Content Comparison

Table of Contents

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Relevance: Users determine how closely the domain data aligns with the Organization's strategic goals. Ratings range from "Very High" (meets/exceeds Level 5 standards) to "Very Low" (meets Level 1 standards), with an option for "Incomplete" if no relevant data exists.
Quality: This assesses the documentation's adherence to industry standards, specifically ISO 9001 for documents. Ratings span from "Very High" (meets/exceeds Level 5 standards) to "Very Low" (meets Level 1 standards), with "Incomplete" indicating non-compliance with any standard. For details, see: https://orthogramic.atlassian. net/wiki/spaces/OUG/pages/edit-v2/233078785?draftShareId=13f5f7a2-d3bb-4d7d-bee5-6647f2aeed12#Assessing-document-quality-in-terms-of-ISO-9001
Quantity: Users evaluate the comprehensiveness of the documentation against ISO 9001 for documents requirements. The scale goes from "Very High" (meets/exceeds Level 5 standards) to "Very Low" (meeting Level 1 requirements), with "Incomplete" for insufficient documentation.

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Quality assessment criteria

Category	Subcategory	Description	Yes/No
Structure and Content	Quality Manual	Included and comprehensive
	Quality Policy and Objectives	Clearly stated
	Procedures and Work Instructions	Detailed and complete
Control of Documented Information	Approval	Document approved for use
	Review and Update	Regularly reviewed and updated
	Identification and Distribution	Clearly identified and appropriately distributed
Accessibility and Storage	Accessibility	Easily accessible to relevant personnel
	Storage and Protection	Properly stored and protected
Retention and Disposal	Retention	Retained for required period
	Disposal	Proper disposal procedures in place
Accuracy and Currency	Accuracy	Accurate and error-free
	Currency	Up-to-date with recent changes
Compliance	Regulatory Requirements	Compliant with relevant regulations

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The normalised criteria scores serve as inputs for Document Weighting, ensuring the weighted score computation remains consistent across document evaluations.
By normalising scores before weighting, the document evaluation process maintains robustness, preventing bias due to variations in document characteristics.

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