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Relevance: Users determine how closely the domain data aligns with the Organization's strategic goals. Ratings range from "Very High" (direct alignmentmeets/exceeds Level 5 standards) to "Very Low" (minimal supportmeets 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" (surpassing meets/exceeds Level 5 requirementsstandards) 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.
Example
Document | Raw Score (Criterion A) | Normalised Score (Min-Max) |
|---|---|---|
Doc 1 | 30 | 0.25 |
Doc 2 | 50 | 0.75 |
Doc 3 | 40 | 0.50 |
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