How to analyse the internal audit finding in term of discrepancy

C

chiaap

#1
hi. i'd like to know how to analyse the internal audit finding in term of descrepacy.
my current company, the my-colleague who has sleft this company, used to calculate in percentage of discrepancy.
% of discrepancy = total discrepacy / total items audited.
total discrepancy is very easy to get by the number of CAR or NCR. but i face a difficulty that the "total items audited" is very subjective and abstract. He said that he took every "shall" word in the ISO 9001 standard as 1 item. sometimes take every PARA in my company internal spec as 1 item.
Noted that ISO9001 required process approached audit method. i do not agree that this is "countable".
My ex-companies, never do the internal audit analysis by percentage. They did the analysis by only breakdown to the NCR issued to each area.

Is the analyse by percentage important for the analysis? May i know the common way for analysis the audit result?

Thanks. :)
 
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Wes Bucey

Quite Involved in Discussions
#2
Thread moved

Thread moved to Auditing including ISO 19011 as more appropriate, since question primarily deals with auditing, rather than doing statistical analysis.
Wes Bucey

by the way, Welcome to the Cove, chiaap!:bigwave:
I hope your question gets more action in this Forum.
 

Spanner

Starting to get Involved
#3
Where is the value?

I can't see the value of reporting a % discrepancy. I analyse audit findings into corrective and preventive actions. The corrective where things do not conform and preventive are really improvements to the system ie things haven't gone wrong yet but they could in the future. I then do a further breakdown into category eg documentation, lack of training, not following procedures, inadequate system etc.

I prepare a simple pareto chart and report on any trends at the management review that are evident across the business eg training may be an issue across several departments or areas .

The overall numbers or percentage of non-conformances are not that important, its the value of the improvements they drive that are important. If a lot of emphasis is placed on the numbers or percentages these will become the focus of attention rather than the real benefits of auditing. There is a temptation to manipulate numbers to keep the percentage up or down depending on your viewpoint.
 

SteelMaiden

Super Moderator
Super Moderator
#4
Spanner said:
I can't see the value of reporting a % discrepancy.
Spanner makes some very good points. By just finding a % discrepancy, you are not doing any analysis at all (when it comes to auditing). Your analysis needs to focus on why, not how many or what percentage. If you find that most of your nonconformances are due to lack of training, step up your training program. If the root causes point to personnel not using the system, then you have some systemic issues with commitment to the system. Don't waste time making fancy charts, graphs, etc. that do not help you get better. Put your effort where it will pay off for your systems. Good luck!
 
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Jen Kirley

Quality and Auditing Expert
Staff member
Admin
#5
Gathering such a pool of system-wide data makes me wonder if:

1. The numbers of discrepancies are so massive that reduction efforts are tracked as an organization moves toward any resemblance of compliance.

2. The audit function is trying to justify its own value, or of quality's value.

I agree with Spanner's message, but organizations mature as they go through the systems assessment process. During the growth stage I expect there could be many discrepancies. A desire to track them, communicate them visually and show progress through reductions seems worthy if the data are used to show progress and not to punish.

Tracking numbers of discrepancies must have a distinct point to be valuable. If you want to show meaningful progress in compliance, consider showing it as broken down by element or as a result of an improvment effort such as mistake-proofing a process.

You can use a spreadsheet for such counts, and make graphs. But I caution that such data should be taken and tracked over rather long periods, to ensure true improvement is taking place and has longetivity.
 
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