Leaving Footprints in the Data - Large Database Validation

M

Mnts2C

#1
Hello,

Currently working as an audit manager in a shipyard. We have a large database where deficiencies are entered from various sources, over 60,000 entries per year. Seems to be a normal, large database that allows a variety of analyses.

One issue under discussion is the value of entering data where something occurred and had no deficiencies. Roughly, the database records deficiencies as level 4 = no deficiency, level 3 = minor, level 2 = major, and level 1 = critical.

It takes effort to ensure the accuracy and validity of the database. One opinion is that the effort to validate level 4 entries is non-value added. Another opinion is that the level 4s provide a relation to deficiencies in similar areas. (ex: two level 2s for the year = better take action now. But two level 2s in relation to 48 no deficiencies = the process seems manageable.) Recording the level 4s can be referred to leaving footprints.

Was hoping some Covers would share some experience on the issue. Thoughts ??

Thanks in advance !!
 
Elsmar Forum Sponsor

Miner

Forum Moderator
Staff member
Admin
#2
A lot depends on what you intend on doing with the data. What you currently have is sufficient for analyses (e.g., Pareto) of the audit deficiencies themselves. However, you limit other analyses that depend on the number of level 4 audits, such as the percentage of discrepancies.

In other words, you have evidence of things done wrong, but no evidence of things done right (i.e., effectiveness).
 

Ninja

Looking for Reality
Trusted Information Resource
#3
Another way to look at this is "negative record".

Being a company making stuff or doing stuff, I presume there is a record already of how many of each thing was done...either in the work logs, or Invoice line items, or completed job tickets, or something...

If 500,000 "jobs" were done, and 60,000 non-4 records were created, it may be good enough to assume that the lack of record for the other 440,000 are 4's.
Not a positive record of no defect...a "negative record" or no defect...and that approach while a bit ethereal may be the most value for what you're trying to analyze.

Positive records are more compelling...but positive records cost money to create.
 
M

Mnts2C

#4
Thank you both.

Ninja is highlighting one facet of the discussion where data, no matter if the data is negative or positive, there is a cost associated with the data.

Is the cost of negative data or footprints worth the effort or ROI?

Good input, thanks.
 

Ninja

Looking for Reality
Trusted Information Resource
#5
FWIW, the type of negative record (meaning "lack of data" being used to guide a decision) is free....
It may, however, be worth as much as it cost.

If you do nothing, you have your negative record which you can use to presume something. Doing nothing is free in this context.
{maybe not reliable...but free none-the-less}
 

Sidney Vianna

Post Responsibly
Staff member
Admin
#6
Mnts2C said:
hoping some Covers would share some experience on the issue. Thoughts!!
If the organization truly embraces the preventive action approach and has the resources to timely analyze the events level 4 (near misses/incidents), it should benefit from this data collection and analysis. The loss causation pyramid model shows that.

But, if level 4 events are not being analyzed, then, I agree, it is a wasted effort.
 

Mark Meer

Trusted Information Resource
#7
I agree with previous replies: no analysis or purpose, no point.

It takes effort to ensure the accuracy and validity of the database. One opinion is that the effort to validate level 4 entries is non-value added.
That being said, IF you do have some marginal use for it (like the example you give), perhaps it is possible to decrease the requirements for entries of this level?

In other words, why does data validation take so much effort? For the actual deficiencies, presumably it is because there is a bunch of required data to be entered. ...but for level 4, perhaps most of this data is unnecessary (because you don't have to detail a deficiency, evaluate it, take actions, etc...).

If your system allows for data requirements for this level to be scaled back, you could potentially keep logging them, without the validation overhead.

MM
 
Thread starter Similar threads Forum Replies Date
A Rate of Staff Leaving the Organization vs. Staff Joining the Organization Benchmarking 4
hogheavenfarm Potential Employer Questions Reason for Leaving Career and Occupation Discussions 37
C Dial Bore Gage Contact Points leaving witness/burnish marks General Measurement Device and Calibration Topics 10
Howard Atkins Leaving Gdansk Imported Legacy Blogs 1
Wes Bucey Leaving a job WITHOUT burning bridges Career and Occupation Discussions 7
C Supervisor leaving team leaders frustrated, skips delegating work to them Career and Occupation Discussions 16
S Tell the Auditor the Management Representative (MR) is Leaving? IATF 16949 - Automotive Quality Systems Standard 29
Proud Liberal Leaving the Quality profession after 25 years Career and Occupation Discussions 38
L Carbon Footprints Tracking examples Sustainability, Green Initiatives and Ecology 2
Fjalar ISO 20417:2021: Technical Data (6.6.4 c) Other Medical Device Related Standards 0
Z PMS Data collection for SAMD SaaS from clients EU Medical Device Regulations 3
S How too Bulk data upload on EUDAMED EU Medical Device Regulations 5
M Validation of Data verification tool per 21 CFR 820 Quality Assurance and Compliance Software Tools and Solutions 1
J Stage 2 audit initial cert, few data points ISO 13485:2016 - Medical Device Quality Management Systems 4
placebo_master Risks of executing a verification protocol against existing data ISO 13485:2016 - Medical Device Quality Management Systems 4
Z Why Control Limits are not the same depending on type of exclusion of data points Using Minitab Software 7
D Question: How to analyze numerical and attribute data Reliability Analysis - Predictions, Testing and Standards 11
N Simple statistics questions on labor data Statistical Analysis Tools, Techniques and SPC 2
T Data verbiage Inspection, Prints (Drawings), Testing, Sampling and Related Topics 6
S QR/2D Codes & Data Strings Misc. Quality Assurance and Business Systems Related Topics 1
A Need to calculate tolerance Intervals with a set of non-normal data and 3-Parameter Weibull distribution Using Minitab Software 0
B GR&R Destructive Data Analysis Gage R&R (GR&R) and MSA (Measurement Systems Analysis) 13
E Raw data retention for Diagnosis Results EU Medical Device Regulations 4
Y Exporting data to the cloud is a "Significant Change"? EU Medical Device Regulations 5
Z Data sheet from McMasterCarr enough for RoHS/REACH documentation? REACH and RoHS Conversations 4
S Eudamed data fields EU Medical Device Regulations 5
J Need Help with FPY Data in Assembly Process Manufacturing and Related Processes 7
Q AMS 2750 E or F Continuous Furnace TUS Data Collection AS9100, IAQG, NADCAP and Aerospace related Standards and Requirements 5
M Reduce occurrence rating based on the PMS data and customer complaint data ISO 14971 - Medical Device Risk Management 2
J Customer Complaint & SCAR, false data Nonconformance and Corrective Action 14
Brizilla Employee Data Privacy Policy - ISO 9001:2015 requirement(s)? ISO 9000, ISO 9001, and ISO 9004 Quality Management Systems Standards 6
D Safety data sheets software REACH and RoHS Conversations 3
M Data Protection and Privacy Policy - looking for a template/example EU Medical Device Regulations 1
S Non parametric test for semi-quantitative data. Statistical Analysis Tools, Techniques and SPC 5
M Disabling measurement data during fault conditions IEC 60601 - Medical Electrical Equipment Safety Standards Series 5
C EU MDR - Annex II 6.1 Pre-clinical and clinical data EU Medical Device Regulations 4
P Ppk results shown as asterisk after the transformation of Non-normal data Using Minitab Software 4
lanley liao How to correctly understand the bullet list d) of 6.3 Analysis of Data for API Spec Q1 Oil and Gas Industry Standards and Regulations 7
Steve Prevette Informational I am presenting a webinar Thursday - "Data Driven Decision Making" - 19 November 2020 Statistical Analysis Tools, Techniques and SPC 5
qualprod Best practice to ensure inputting of data in production Lean in Manufacturing and Service Industries 19
D Preservation of Electronic Data / Information Technology ISO 13485:2016 - Medical Device Quality Management Systems 5
M Comparing data from destructive testing Inspection, Prints (Drawings), Testing, Sampling and Related Topics 7
DuncanGibbons Technical Data Package vs Digital Product Definition APQP and PPAP 0
Z Putting back excluded rows/data points in a control chart Using Minitab Software 0
F General Data Protection Regulation (GDRP) CE Marking (Conformité Européene) / CB Scheme 6
Z Minitab - Updating Graph with specific data points Using Minitab Software 2
E PEMS Hazards - IEC 60601 Clause 14.6 - Internal data use - Pressure sensor IEC 60601 - Medical Electrical Equipment Safety Standards Series 3
K Transform variable data into attribute data Reliability Analysis - Predictions, Testing and Standards 24
R Clinical evaluation without clinical data - MDR Article 61(10) EU Medical Device Regulations 9
H Capability Data for Paint Thickness on Painted Parts Statistical Analysis Tools, Techniques and SPC 10

Similar threads

Top Bottom