Leaving Footprints in the Data - Large Database Validation

Mnts2C

Starting to get Involved
#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.
 

Mnts2C

Starting to get Involved
#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
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 6
H Capability Data for Paint Thickness on Painted Parts Statistical Analysis Tools, Techniques and SPC 10
D BS EN 62304 - Medical-Relevant Data C.5 - Definition of IEC 62304 - Medical Device Software Life Cycle Processes 5
T Submitting MR Compatibility Data for 510(k) Cleared Device Other Medical Device and Orthopedic Related Topics 2
S Quality manager considering data science Quality Manager and Management Related Issues 19
A What are Practical data center best practices IEC 27001 - Information Security Management Systems (ISMS) 0
U Do we need clinical trial data for Class IIa medical device under MDR EU Medical Device Regulations 7
S Average and standard deviation of Cumulative Data Statistical Analysis Tools, Techniques and SPC 5
V IS/ISO/IEC 17025:2017 Clause 7, sub clause 7.11 Control of data and information management ISO 17025 related Discussions 1
Watchcat CERs Literature Databases - Searching for data to evaluate EU Medical Device Regulations 16
D Transformation of Data Normality Failed Using Minitab Software 11
J Sample size for creating a data base as a reference to a tested variable Other Medical Device and Orthopedic Related Topics 6
M GUDID data deficiency communication - IS THIS A SCAM? ISO 13485:2016 - Medical Device Quality Management Systems 29
H Question about implications of performing Firmware upgrade via MDDS - Medical Device Data Systems 21 CFR Part 820 - US FDA Quality System Regulations (QSR) 2
R Demonstrate how sufficient levels of access to data is achieved - Claims of equivalence EU Medical Device Regulations 3
R Material safety data sheet (MSDS) related clause in IATF 16949 manual IATF 16949 - Automotive Quality Systems Standard 17
CPhelan Using clinical trial safety data for evidence for CE marking EU Medical Device Regulations 7
M Informational US FDA – MDR Data Files – Alternative Summary Report Data Since 1999 Available Medical Device and FDA Regulations and Standards News 0
CPhelan Do you require MDSAP for CE Marking of a Medical Device or is ISO13485:2016 with clinical data sufficient? CE Marking (Conformité Européene) / CB Scheme 5
M Data analysis Design of Experiments Using Minitab Software 3
S Seeking efficient method to manage install base data Manufacturing and Related Processes 0
V Every good documentation practice observation is an data integrity issue US Food and Drug Administration (FDA) 7
M Informational US – National Evaluation System for Health Technology Coordinating Center (NESTcc) Solicits Public Comments for Data Quality and Methods Frameworks Medical Device and FDA Regulations and Standards News 0
M Informational Eudamed Data Exchange Guidelines Medical Device and FDA Regulations and Standards News 0
M Informational EU – Eudamed Data exchange services and entity models introductions Medical Device and FDA Regulations and Standards News 4
M Informational EU – M2M Data Exchange available services for accessing MDR EUDAMED data available for Economic Operator (EO) organisations Medical Device and FDA Regulations and Standards News 0
V What is the criteria to cite an good documentation practices observation as an data integrity related issue US Food and Drug Administration (FDA) 6
D Do we need normal data for gage r&r studies? Gage R&R (GR&R) and MSA (Measurement Systems Analysis) 5
M Automatic Data Gathering Requirements and Privacy Implications Medical Information Technology, Medical Software and Health Informatics 0
R Over read of physiological data by technicians EU Medical Device Regulations 0
L How to evaluate the process capability of a data set that is non-normal (cannot be transformed and does not fit any known distribution)? Capability, Accuracy and Stability - Processes, Machines, etc. 12
M Informational EU – EUDAMED UDI Device Data Dictionary + data sets Medical Device and FDA Regulations and Standards News 0
F Mig Welded Components - IMDS International Material Data System RoHS, REACH, ELV, IMDS and Restricted Substances 1
L SPC - Methods to collect data IATF 16949 - Automotive Quality Systems Standard 7
M Informational MDCG 2019-4 Timelines for registration of device data elements in EUDAMED Medical Device and FDA Regulations and Standards News 0

Similar threads

Top Bottom