Data Points expressed in %
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 This topic has 14 replies, 12 voices, and was last updated 18 years, 2 months ago by Jonathon L. Andell.

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May 14, 2004 at 11:30 am #35540
Hi,
If we measure our data points as % ( eg % of hit ratio, or % of Customer statisfaction) what is the nature of the data? Continous or attribute?
regards
Nik0May 14, 2004 at 1:02 pm #100270The data is Attribute….
0May 17, 2004 at 7:17 am #100323
curiousParticipant@curious Include @curious in your post and this person will
be notified via email.The Data technically is Attribute, but can be treated as a psuedo continous and can use tools used for continous data for analysis
hope this helps0May 17, 2004 at 10:19 am #100326
R VermaParticipant@RVerma Include @RVerma in your post and this person will
be notified via email.The purpose of drawing a process map is:
Uncover deficiencies.
To clarify process steps.
Get a visual picture.
All of the above.
0May 17, 2004 at 10:36 am #100331I agree with you,regards
0May 17, 2004 at 10:54 am #100334
R VermaParticipant@RVerma Include @RVerma in your post and this person will
be notified via email.The purpose of drawing a TQM Process Map is:
Uncover deficiencies.
To clarify process steps.
Get a visual picture.
All of the above.0May 17, 2004 at 11:32 pm #100391
Chris SeiderParticipant@cseider Include @cseider in your post and this person will
be notified via email.Nik, I’m curious the reason for the question whether a process outputing a % of x is an attribute or continuous. I disagree with the answer you received earlier and consider it to be continuous.
0May 17, 2004 at 11:46 pm #100397
Ken FeldmanParticipant@Darth Include @Darth in your post and this person will
be notified via email.Whether a % should be considered discrete or continuous may have more to do with the characteristic of the underlying metric rather than the fact you can carry a percentage out to many decimal places. What constitutes the numerator and denominator is what is important. If the numerator and denominator are discrete data…sale/no sale divided by the number of sales calls…then the resulting ratio doesn’t suddenly become continuous. If the numerator and denominator are continuous…minutes of downtime divided by total minutes..then the resulting ratio might be considered continuous. In some cases, percentages can be put on an I/MR chart which by nature is continuous even if the ratio is truly discrete.
0May 18, 2004 at 10:53 am #100404Ok, My problem, is i am measuring a concession metric, it is
Total amount of discount given divided by no of calls received. I need to plot on a control chart to check the process control, as process is designed to have certain % of concession as acceptable limits. Basically we try to save the sale.
rgds//Nik0May 18, 2004 at 12:07 pm #100406
Ken FeldmanParticipant@Darth Include @Darth in your post and this person will
be notified via email.That’s a little trickier. I assume you have dollars over calls so your proportion represents dollars/call for some time period. I assume this ratio could be greater than 1. I don’t know what would constitute a reasonable frequency to report it out nor whether there would be any rational subgroup which could be made. I would be inclinded to try an IMR possibly by day to start with and see how it looks. There might be further interest to look for Components of Variation and see if it varies by Call Center or Type of Call or Phone Associate, etc. I also assume you won’t be putting the “acceptable limits” on the control chart.
0June 10, 2004 at 7:45 am #101479
Michael SchlueterParticipant@MichaelSchlueter Include @MichaelSchlueter in your post and this person will
be notified via email.Nik,
At least % is something you should avoid when doing improvement activities.
The discussion gives no clear answer to your question; even worse, % won’t give you much insight into the process you try understanding or improving.
% is nonspecific. Most of the time you can be more specific and gain resolution power.
However, % are ok to summarize progress:summarizing is more global and less specific.
Kind regards, Michael Schlueter0June 10, 2004 at 12:23 pm #101485Mike,
Won’t the percentage give me a sigma level (convert % to sigma)?0June 10, 2004 at 12:27 pm #101486
SphynxrasMember@Sphynxras Include @Sphynxras in your post and this person will
be notified via email.I have dealt with the data as continuous in my most recent project…(process recovery rates, which are percentages), and had no issues treating the data as continuous.
sphynxras0June 10, 2004 at 12:43 pm #101490The answer is, yes, if you are measuring level of performance, such as % defective, or % ontime delivery where 100% is your goal. If your % is based on ratios of continuous data, like % moisture or % butterfat, it has nothing to do with sigma of your process.
As implied in previous posts, you can even treat % of attribute measures as if it is continuous data — sometimes. To work, it should ‘look like’ continuous, seminormal data, i.e., with % wellspread and not close to 1 (or 0).
Suggest: Just go do it. Treat % as continuous data in your analysis BUT know and understand that you are violating the assumptions inherent to a valid analysis. Get all the insights you can from the analysis, but use your results with great caution.0June 11, 2004 at 1:02 am #101551
Jonathon L. AndellParticipant@JonathonL.Andell Include @JonathonL.Andell in your post and this person will
be notified via email.Officially, # of discounts / # of calls is a proportion, which officially is attributebased. Unofficially, if there are high call volumes (hundreds per time period), and reasonably high discount volumes (at least 25 per time period), the data could be handled as semicontinuous. The Statistics Police won’t drag you off in the middle of the night.
However, as others point out, you might want to consider another metric based in dollars. Maybe it’s dollars of discount per dollars of related pricing. Except for those who fret that pennies cannot be subdivided, most practitioners would consider that truly continuous. More importantly, you’d be connecting with the “real” business impact of the discounts, and you’d have a relatively easy time demonstrating cost savings as increases in net revenue.0 
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