PPM calculation of customer complaints for PMS


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Hi Bill and Bev, thanks for the input.

I will look into it. The c-chart explanation gave me some ideas to work with.
Bev based on what do you think is best to define the time interval for use?

According to the new EU MDR and ISO 13485 we need to monitor the risk in the market (PMS / Post production feedback), as I understood against the difined risks levels (which include indeed risks that are not acceptable at any level).

Maybe I emphasized to much on ppm. I'm seeking a way to calculate risk levels for PMS, given the delay of customer feedback, that makes sense.
And additional will not be influenced by an increasing sales volume.

I have some ideas for the c-chart but any other suggestion is welcome.


We calculated the average days of delay between Sale and Complaint (did this by modeliing new release to the market). Then we just put a lag on the sales data. If you are comparing June complaints to June sales...you are really comparing June complaints to April Sales. That is how we account for the lag. It is not 100% perfect but it is a better estimation than not estimating at all.

Bev D

Heretical Statistician
Super Moderator
I have been fortunate enough to work industries where serial numbers were used so we could tie the complaints to manufacturing dates (usually months) to keep the complaints/defects aligned as sales were often lagging manufacturing. We also used a form of survival rate chart to account for usage and seasonality. I’ve posted on this approach several times here…
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