Hi,

In what all scenario P75/3rd quartile measurement is relevant? For example in Pizza delivery case if we measure mean as the central tendency and try to bring in improvement, there will be extreme scenarios which will have large delivery time due to unavoidable causes. This will shift the mean from required mean. In this case should I measure and monitor P75? and if my P75 is always within required level then does this conclude that my delivery performance is stable? or I should consider variance and deviations?

 

Regards

Jyotiram

Hello Jyotiram,

The key is to know about normality. If the data is normally distributed, mean and standard deviation shall give you sufficient information about the process performance.

However, if the data is not normally distributed, median and range may be used to understand the performance. If you get quartile values (P75, P50, P25) in addition to max and min, you get additional information about the data.

Now coming to your question, P75 provides you a number that has 75% values below it (or 25% values above it). This is limited information.

If P75 (Q3) is 20 minutes, you know that 75% values are within 20 minutes in pizza delivery process. This however does not tell you how many values are say, beyond 30 minutes (which may be the promised delivery time). Even if you know that data is normally distributed, P75 value alone does not give you enough meaningful information to reach any inference.

I hope I have answered your question. Do get back if you need any further information.

Thanks for your input. It's quite useful. Let me give my realtime scenario where I have the challenge. I run the IT support service center. My team handles simple to very complex customer technical problems. I track the time to resolution of each of the problem. Due to the complex technical issues, mean is always very high. This is due to few outliers which take long time to resolve or has huge external variables involved. Hence I track trend of p75 performance and use the control chart for this trend. I really can't control the external variables neither the very complex issues which will definitely take time. I don't track the standard deviation neither the mean. Do you think what I am following is the right approach?

Dear Jyoti,

Its a good Idea to have control charts on P75, however do you have exact details of enlisted causes for high TAT (which you have termed as external). If any problems are out of scope for your process you would like to make a note of how many of these are due to interdepartmental delays, customer awareness, demands beyond product specs. etc...

This will provide you with answers as to where you need to take actions in case of high TATs

It would be a good idea to maintain a FMEA as a live document for your process

It is difficult for me to comment whether using P75 alone is sufficient. P75 is similar to  median (which is P50). As you have outliers, it may be good to look at P75. 

There may be opportunities to focus on primary reasons for those extreme values which are hurting the predictability in your process. You may like to convert such reasons into Six Sigma projects. Working project by project, you may be able to improve the situation substantially.