Profession Management System

This document provides the ultimate guide to the Profession Management System, covering every aspect from basic concepts to advanced configuration. It ensures users can effectively manage, standardize, and enhance their profession hierarchies with a comprehensive understanding of the system's capabilities.

1. System Overview: Core Components Defined

Component	Purpose	Examples	Key Considerations
Local Professions	Job titles specific to your organization, reflecting unique structure and terminology. They provide a granular view of roles within your company.	"HR Specialist," "Finance Assistant," "Senior Widget Designer," "Regional Sales Coordinator," "Software Developer III," "Lead Project Architect"	Maintain consistency in local profession naming conventions. Regularly review and update local professions to reflect organizational changes.
Global Professions	Standardized job titles shared across organizations or defined by an industry standard. Facilitates reporting, comparison, and benchmarking across different entities.	"Human Resources Manager," "Financial Analyst," "Software Engineer," "Project Manager," "Data Scientist," "Cybersecurity Analyst"	Choose a global profession taxonomy that aligns with your industry and reporting needs. Establish a process for adding new global professions as needed.
Local Categories	Organizational groupings for local professions, classifying job titles within your company's specific context. They provide a structure for reporting and analysis.	"Administration," "Technical Support," "Marketing," "Sales," "Engineering," "Customer Service," "Operations," "Research & Development"	Align local categories with your organizational structure and reporting requirements. Ensure that each local profession is assigned to the appropriate category.
Global Categories	Standardized groupings for professions, enabling cross-organizational comparisons. Often based on industry standards or common functional areas.	"Human Resources," "Finance," "Information Technology," "Project Management," "Sales & Marketing," "Operations," "Research & Development," "Legal"	Select a global category taxonomy that aligns with industry standards and your reporting needs. Establish a process for mapping local categories to global categories.
Identity Links	Connections between individuals and their assigned professions, establishing the relationship between an employee and their current role within the organization.	"Jane Smith" → "Project Manager," "John Doe" → "Software Engineer," "Alice Brown" → "HR Specialist," "Bob Johnson" → "Senior Sales Manager"	Regularly review and update identity links to reflect employee promotions, transfers, and departures. Implement a process for ensuring that all employees have accurate and up-to-date identity links. Consider integration with your HRIS system for automated updates.

2. Merging Methods: A Comprehensive Comparison

Method	What It Does	When To Use	Limitations	Example Scenario	Granularity	Pre-Merge Analysis
Bulk Auto-Merge	Automatically merges all eligible local professions with similar global professions based on the configured similarity threshold and other settings.	When you need to standardize the entire system quickly and are confident in the accuracy of the matching algorithm. Always preview.	Offers the least control over individual matches. Requires careful configuration and thorough previewing to avoid unintended merges. High risk of incorrect categorizations if validation is skipped or superficial. May overload the system during peak hours. Rollback is possible but complex.	After a company acquisition, you want to quickly align all job titles of the acquired company with the standardized titles of the parent company.	System-wide	REQUIRED
Selected Auto-Merge	Merges only the local professions that you have specifically selected with their best matching global profession.	When you want targeted standardization and need more control over which professions are merged. Ideal for standardizing specific departments or job families.	Requires manual selection of professions beforehand. Still relies on the matching algorithm, so may not always produce the desired result. Limited to preselected professions, potentially missing related roles. May not handle complex scenarios involving multiple potential matches.	Standardizing job titles within a specific department, like the IT department, while leaving other departments untouched.	Selection-based	Recommended
Manual Merge	Allows you to directly choose which local profession merges with which global profession, providing complete control over the merging process.	When automatic matching fails or when you need to merge specialized roles that have no obvious automated match. Also, use for correcting errors made by automated merges or for handling exceptions.	Time-consuming, especially for large datasets. Requires a deep understanding of both local and global profession hierarchies. Prone to human error if not carefully reviewed. Can be tedious for large numbers of merges.	Merging highly specialized roles, such as "Senior Quantum Computing Specialist," with a global title that doesn't perfectly capture the nuances of the local role. Also useful for remapping titles after an incorrect auto-merge.	Profession-by-profession	Highly Recommended
Direct Pair Merge	Merges any two professions together, regardless of their type (local or global) or similarity. For advanced use cases that bypass all automated logic.	For special cases, corrections, or when you need to combine two global titles that represent the same role after a system update or correction. This bypasses the standard matching algorithm completely. Advanced system use only.	Requires extreme caution. Bypasses all matching logic and safeguards. Should only be used by highly experienced administrators with a deep understanding of the data. Easy to introduce data inconsistencies and errors. No automatic rollback.	Combining two global titles, such as "Software Engineer" and "Software Developer," after realizing they represent the same role and you want to consolidate them. Or correcting a major data error.	Pair-wise	CRITICAL! Thorough validation.

3. Matching Intelligence: Inside the Algorithm's Mind

The system's matching algorithm is the engine that drives automated standardization. It leverages a configurable similarity threshold (default 90%, adjustable from 80-100%) and advanced text analysis techniques to identify potential matches.

• Similarity Threshold: The similarity threshold sets the stringency of the matching process. Higher thresholds demand closer matches, reducing false positives but potentially overlooking valid matches with slight variations. Lower thresholds increase the number of potential matches but also increase the risk of incorrect merges. Balancing precision and recall requires careful tuning. Consider A/B testing to evaluate the best threshold for each use case.
• Language Support: Multilingual support is critical for global organizations. The system analyzes text in both local and global languages to identify the best possible match, considering linguistic nuances and cultural differences in job title conventions.
• Customizable Weights: The weights applied to each language, as well as specific keywords or phrases, can be customized to reflect the unique characteristics of your data. For example, you can assign higher weights to certain keywords that are considered more important in your industry.

Detailed Matching Logic Examples:

Match Scenario	Example	Match Logic	Result	Notes
Both languages exceed threshold	CS: "Účetní" → "Účetní" (95%)EN: "Accountant" → "Accountant" (95%)	CS similarity > threshold AND EN similarity > threshold	Will merge	This is the ideal scenario, indicating a strong match in both languages. High confidence in the accuracy of the merge.
One language exceeds threshold, other empty	CS: "Manažer" → "Manažer" (95%)EN: "" → "Manager" (empty)	CS similarity > threshold AND EN is empty	Will merge	This indicates a strong match in the available language and no conflicting information in the other language. Review recommended to ensure context supports merge.
One language exceeds threshold, other doesn't	CS: "Vedoucí projektu" → "Projektový manažer" (88%)EN: "Project Lead" → "Project Manager" (95%)	EITHER CS similarity > threshold OR EN similarity > threshold	Will merge	This provides flexibility when one language has a clearer match than the other. The higher score is favored. Consider adjusting weights to reflect the relative importance of each language. Review the individual connection
Both languages exist but below threshold	CS: "Asistent" → "Sekretářka" (65%)EN: "Assistant" → "Secretary" (70%)	CS similarity EN: "Global IT Manager" → "IT Manager" (94% after prefix removed)	Prefix "Global" is ignored in the comparison. Similarity is calculated after stripping the prefix.	Will merge
Abbreviated vs. full form	CS: "HR Specialista" → "Personalista" (65%)EN: "HR Specialist" → "Human Resources Specialist" (92%)	EN similarity > threshold	Will merge	The system can recognize and match abbreviated forms to their full equivalents, improving the chances of successful merges. Configure a comprehensive list of abbreviations and their corresponding full forms.
Hyphenated vs. separated words	CS: "Projektový manager" → "Projekt-manager" (93%)EN: "Project Manager" → "Project-Manager" (95%)	Text normalization (removing hyphens and spaces) ensures accurate matching.	Will merge	The system normalizes text to account for variations in hyphenation and spacing, preventing these minor differences from hindering the matching process.
Local Profession is Empty	CS: "" → "Účetní" (empty)EN: "" → "Accountant" (empty)	Both CS and EN are empty.	Won't merge	Prevents matching of non-existent local professions, which is likely an error in the data. Investigate the source of empty local professions and correct the data.
Local and Global are Same But Different Category	CS: "Účetní" → "Účetní" (95%) - Local in "Finance Admin", Global in "Core Finance"EN: "Accountant" → "Accountant" (95%)	CS similarity > threshold AND EN similarity > threshold - Category differs	Will Merge Profession, Category depends on Merge Categories Setting (See Section 7)	Addresses a situation where titles are identical but the job functions, departments or grouping of the job is very different, requiring manual confirmation that it is the right match. Review Identity Connections and adjust category assignments if needed.

4. Configuration Options Matrix: Optimizing Standardization

Option Combination	What Will Happen	Best For	Real-World Example	Detailed Considerations
✓ Merge Categories ✓ Merge Identities ✓ Prefer Global Categories	- Global categories are kept. Local categories are discarded.- People stay connected to professions, with their connections updated to the global profession.- Local professions are removed.	Complete standardization to a global system and streamlined reporting. Enforces a consistent category structure and ensures all employees are associated with standardized roles. Minimizes reporting complexity. Simplifies the taxonomy.	Company-wide reorganization to a standard job framework across all departments and locations, ensuring consistent reporting, career paths, and skills management.	Requires a well-defined and accurate global category taxonomy. May result in loss of valuable information if local categories contain unique details not captured in the global categories. Thorough review of global categories required before merging.
✓ Merge Categories ✓ Merge Identities ✗ Prefer Global Categories	- Local categories are used to create new global categories if a matching global category does not exist.- People stay connected to professions, with their connections updated to the global profession.- Local professions are removed.	Keeping your organizational category structure while standardizing job titles. Allows for maintaining internal organizational structure while adopting standardized job titles. Useful where localized org charts are important. Global titles still provide a standard	Preserving department structure while harmonizing titles during a merger, allowing each department to maintain its specific organizational structure while adopting a common set of job titles.	May result in a proliferation of global categories if local categories are not consistently mapped. Requires a governance process for managing the creation of new global categories.
✗ Merge Categories ✓ Merge Identities Any Preference	- Categories stay separate. Local and global categories are maintained independently.- People stay connected to professions, with their connections updated to the global profession.- Local professions are removed.	Standardizing titles while maintaining your existing category system. Allows for adopting standardized job titles without disrupting your existing organizational structure. Preserves reporting at the local level while adhering to global naming standards.	Harmonizing job titles across different divisions, each with its unique organizational structure and reporting requirements. Each division can maintain its internal taxonomy while reporting standard titles	Requires careful maintenance of both local and global category systems. Increases complexity in reporting and analysis. May lead to inconsistencies if local and global categories are not aligned.
Any Categories Setting ✗ Merge Identities Any Preference	- Categories are handled per the configured settings.- People's connections remain unchanged. No identity links are modified.- Local professions are removed.	Testing merges without affecting people's connections. Useful for previewing and simulations to assess the impact of standardization before committing to changes. Safest option for initial testing. Non-destructive. Does not affect people's profiles.	Previewing the impact of standardization on job titles and categories without affecting employee records or HR systems. This allows for identifying potential issues before making changes to the live data. "What-If" simulations are enabled	Essential for validation and risk mitigation. Allows for identifying potential issues before they impact employee data. Enables stakeholders to review the proposed changes and provide feedback. Highly recommended as a first step.
✓ Merge Categories ✗ Merge Identities ✓ Prefer Global Categories (Testing Combination)	- Global Categories are preferred. - Identity links are not touched. - Testing and simulation of category merges without impacting personnel assignments.	For simulation of a Category merge, as described above, prior to actioning it. Testing merge without disrupting existing connections. Testing, Validation, and preview.	An organization wants to test a category and taxonomy merge without touching the employee records. "What-If" simulations are enabled	Category merge requires accurate taxonomy. Simulation ensures minimal impact.
✓ Merge Categories ✗ Merge Identities ✗ Prefer Global Categories (Testing Combination)	- Local categories create new global ones where they don't exist. - Identity links are not touched. - Testing and simulation of category merges without impacting personnel assignments.	For simulation of a Category merge, as described above, prior to actioning it. Testing merge without disrupting existing connections. Testing, Validation, and preview.	An organization wants to test a category and taxonomy merge without touching the employee records. "What-If" simulations are enabled	Category generation requires accurate and validated source data. Simulation ensures minimal impact.

5. Similarity Threshold Effects: Balancing Precision and Recall (Expanded)

Threshold	Strictness	When to Use	Example	Potential Results	Mitigation Strategies
95-100%	Very strict	For critical professions where precision is paramount, and minimal ambiguity is acceptable. This is suitable for high-level positions, specialized roles, or when regulatory compliance requires exact matches.	C-Suite positions (e.g., "Chief Financial Officer"), specialized medical roles (e.g., "Cardiothoracic Surgeon"), legal titles (e.g., "Senior Legal Counsel").	"Chief Financial Officer" will only match "Chief Financial Officer." This minimizes false positives and ensures that only identical titles are merged. May result in a smaller number of matches, requiring manual intervention for variations.	Implement a robust exception handling process for manual review and merging of titles that fall just below the threshold. Consider creating a synonym list for common variations.
90-94%	Default (Balanced)	For general use in most organizations. Provides a good balance between precision and the number of potential matches. This setting is suitable for standard corporate roles where minor variations in titles are acceptable.	Standard corporate roles (e.g., "Marketing Manager," "Software Engineer," "Project Manager").	"Marketing Manager" may match "Marketing Director," "Marketing Management Specialist," or "Senior Marketing Manager." This allows for some flexibility while maintaining a reasonable level of accuracy. Review all proposed matches	Carefully review all proposed matches before committing to the merge. Establish clear guidelines for acceptable title variations. Consider using a validation checklist to ensure that all matches meet the defined criteria.
80-89%	More flexible	When finding a larger number of potential matches is desired, even if it means accepting slightly less precise matches. Use with extreme caution and with careful previewing. This setting may be appropriate for support roles, general staff positions, or when dealing with legacy data that contains inconsistencies.	Support or general staff roles (e.g., "Administrative Assistant"), roles with many variations (e.g. Sales roles), or when dealing with legacy data that may have inconsistencies.	"Administrative Assistant" might match "Office Assistant," "Admin Support," "Clerk," or even "Receptionist." Requires extreme care to avoid merging unrelated professions. The risk of false positives is significantly higher, requiring thorough validation.	Implement a multi-stage validation process involving multiple stakeholders. Use a detailed scoring system to evaluate the quality of each proposed match. Document the rationale for accepting or rejecting each match. Conduct a post-merge audit to identify and correct any errors.
<80%	Very Flexible	When a extremely broad match and discovery is needed, possibly when setting up a new taxonomy or job architecture. High risk of mismatching, requiring the use of manual merge for most operations.	In an early startup, attempting to relate all jobs with "Engineer" somewhere in the local title to standardized "Software Engineer".	"Junior Developer" might match "IT Support", "Hardware Technician", or even "Civil Engineer" as the weighting on "Engineer" is so high. Very high rate of false-positives requiring extensive review and manual merge to correct.	Avoid using this threshold in production environments. Use it only for exploratory analysis and taxonomy development. Rely heavily on manual validation and never perform bulk merges at this threshold. Consider it an "experimental" mode

6. Step-by-Step Merge Process: A Deep Dive

Step	What Happens	UI Element	Trigger Action	Example	Potential Issues & Mitigation	Validation Checks
1. Preparation	The system analyzes all local and global professions, categories, and identity links. Data is loaded into memory for analysis.	N/A	(Automatic) System initialization	500 local vs. 300 global professions, 100 categories, 1000 identity links loaded into memory.	Potential Issue: Large datasets may require significant processing time and memory. Mitigation: Optimize database queries, use efficient data structures (caching), consider running the merge during off-peak hours. Implement progress indicators to provide feedback to the user.	Memory usage, query execution time
2. Matching	The system calculates text similarity scores between local and global professions based on configured settings, the matching logic (Section 3), and text normalization techniques.	N/A	(Automatic) Matching algorithm execution	"Project Manager" → 92% similar to "Project Leader." The system calculates the similarity score based on Levenshtein distance, cosine similarity, and considers language translations using a translation API.	Potential Issue: Abbreviations, acronyms, inconsistent naming conventions, and misspellings may reduce similarity scores. Cultural differences in naming conventions may also lead to inaccurate matches. Mitigation: Use a lower similarity threshold (with extreme caution), manually adjust profession names before merging, create custom matching rules using regular expressions, and implement a thesaurus for synonym matching.	Similarity scores, Levenshtein distance, accuracy of normalization
3. Categorization	Categories are processed based on the selected merge settings (Section 4). Local categories may be merged into global categories, new global categories may be created, or categories may be left untouched.	Checkboxes, Dropdowns, Radio Buttons	User selects "Merge Categories" and "Prefer Global Categories" in the configuration panel.	"IT Support" category may create or match a global category like "Information Technology." If "Prefer Global Categories" is selected, the local "IT Support" category will be merged into the global "Information Technology" category. Otherwise, a new global category "IT Support" might be created.	Potential Issue: Category conflicts may arise if similar category names have different meanings across organizations. Mismatched categories can lead to inaccurate reporting and analysis. Mitigation: Carefully review the preview results and adjust category mappings manually if necessary. Implement a workflow for resolving category conflicts.	Category assignments, number of impacted professions
4. Identity Transfer	The system updates the identity links to connect individuals to the appropriate global professions. Existing links to local professions are replaced with links to the corresponding global professions. This step ensures that employee records are accurately updated with standardized job titles.	N/A	(Automatic) Identity link update process	Jane Smith, who was previously connected to the local profession "Data Analyst," is now connected to the global profession "Data Analyst." The system updates the "employee_professions" table in the database to reflect this change.	Potential Issue: Individuals may have multiple local professions that need to be transferred to the correct global equivalents. Incorrectly transferred identity links can lead to inaccurate employee records and HR data. Mitigation: The system processes each profession independently, ensuring that all relevant identity links are updated. Review the merge results to verify that all connections are accurate. Implement a process for auditing identity link updates.	Number of identity links updated, consistency of identity data
5. Cleanup	The system removes unused or empty local categories and professions. Local professions that have been merged are marked as "Merged" (or deactivated) but retained for historical purposes (Section 12). This step helps to maintain a clean and efficient database.	N/A	(Automatic) Cleanup routine	An empty "Junior Staff" category is deleted. The local profession "Assistant Marketing Manager," which has been merged with the global profession "Marketing Manager," is marked as "Merged" and deactivated.	Potential Issue: Categories or professions with direct identity links may not be automatically removed to avoid disrupting existing connections. Accidental deletion of categories or professions can lead to data loss. Mitigation: The system preserves categories with direct identity links to avoid disrupting existing connections. Review and manually delete orphaned categories or professions if necessary. Implement a process for backing up data before performing cleanup operations.	Number of categories/professions deleted or deactivated, presence of identity links
6. Validation	The system verifies that all updated identity links are valid, and that the database maintains data integrity. This step ensures that the merge operation has not introduced any errors or inconsistencies. The system requires a 95% successful validation rate before committing the changes.	N/A	(Automatic) Validation process	All 450 transferred connections are verified to ensure that they point to valid global professions and categories. The system checks for referential integrity and data consistency.	Potential Issue: Errors during identity link updates may result in broken connections or orphaned records. Data corruption can lead to inaccurate reporting, performance issues, and data loss. Mitigation: The system requires a 95% successful validation rate before committing the changes. If the validation fails, the entire merge operation is rolled back to prevent data corruption. Implement comprehensive data validation routines and data integrity checks.	Validation success rate, number of errors detected, database consistency
7. Preview Merge	The System executes steps 1-6 but does not commit anything to the database. Instead, displays a detailed summary of the proposed changes.	Preview Merge button	User clicks the "Preview Merge" button. The button label is dynamically rendered using the localization key hiko.preview_merge	Review the simulation to check the proposed changes. Review results	Potential Issue: System is misconfigured and incorrectly categorizes/assigns professions. Failure to thoroughly review the preview can lead to errors in the live data. Mitigation: Review the preview results carefully, paying close attention to category assignments and identity links. Use the filtering and sorting options to examine specific subsets of the data. Allow stakeholders to review the preview and provide feedback. Reconfigure system before committing the merge if there is an issue.	Review the simulation, reconfigure the system, and simulate again until the simulation results match expectations
8. Commit Merge	The System executes steps 1-6 and commits the changes to the database. This action makes the changes permanent.	Commit Merge button	User clicks the "Commit Merge" button. Confirmation dialog displays a warning	Execute the merge and commits	Potential Issue: System is misconfigured and incorrectly categorizes/assigns professions. Committing an incorrectly configured merge can lead to widespread data errors and require significant effort to correct. Mitigation: Before committing the merge, ensure that the preview results have been thoroughly reviewed and validated. Back up the database to allow for a rollback in case of errors. Implement change control procedures to manage the merge process.	Last-minute check of all configurations prior to commit to ensure that it is as intended. Database backup. Immediate audit on completion to ensure that the result is as intended.

7. Category Handling Scenarios: Expanded and Clarified

Scenario	With Merge Categories ON	With Merge Categories OFF	Example Case	Detailed Explanation	Business Impact	Mitigation Strategy
Local has category, Global has matching category	Global category is used for merged professions	Categories remain separate. Local professions retain their original local categories.	Local "Finance" merges with global "Finance"	The local profession "Finance Assistant" is merged with the global profession "Financial Analyst." With "Merge Categories ON," both professions are now associated with the global "Finance" category. With "Merge Categories OFF," the local profession retains its local "Finance" category, while the global profession remains in the global "Finance" category.	Streamlined reporting, consistent taxonomy	Validate correct taxonomy, update all links
Local has category, Global has different category	Global category is used if "Prefer Global" is ON. Otherwise, a new global category is created based on the local category.	Categories remain separate. The local and global professions remain in their respective categories.	Local "Accounting" vs. global "Finance"	The local profession "Accounting Clerk" is merged with the global profession "Financial Analyst." If "Prefer Global" is ON, both professions will be associated with the global "Finance" category. Otherwise, a new global category named "Accounting" may be created, and the local profession will be associated with this new category.	Category conflict, accurate accounting may be disrupted.	Evaluate business process for correct impact. Don't merge if needed.
Local has category, Global has none	Global profession remains uncategorized if "Prefer Global" is ON. Otherwise, a new global category is created based on the local category.	Categories remain separate. The local profession remains in its local category, and the global profession remains uncategorized.	Local "Junior Staff" with no global equivalent	The local profession "Junior Staff" is merged with a newly created global profession (e.g., "Entry-Level Employee"). If "Prefer Global" is ON, the global profession will remain uncategorized. Otherwise, a new global category named "Junior Staff" may be created, and the local and global professions will be associated with this category.	Lack of category makes the role difficult to search.	Determine an appropriate global category.
Local has no category, Global has category	Global category is retained and applied to the merged professions	Categories remain separate. The global profession remains in its category, and the local profession remains uncategorized.	An uncategorized local role matches a categorized global role	A local profession "Intern" (uncategorized) is merged with the global profession "Intern," which belongs to the "Student Programs" category. With "Merge Categories ON," the merged profession will be associated with the "Student Programs" category. With "Merge Categories OFF," the local profession remains uncategorized.	Lack of category makes the role difficult to search.	Determine an appropriate global category.
Neither has category	Both remain uncategorized after the merge	Both remain uncategorized. No changes to categories.	Utility or temporary positions without categorization	The local profession "Seasonal Worker" and the global profession "Temporary Employee" are both uncategorized. After the merge, both professions remain uncategorized.	Difficult to manage a wide range of uncategorized roles.	Review the purpose of uncategorized roles, and assign a global category.
Category has other professions	Category is preserved with its remaining professions. Other professions within the category are not affected by the merge.	No change. The category structure remains intact.	"IT" category containing multiple profession types, such as "Network Administrator" and "Help Desk Technician"	The local profession "Software Developer" is merged with the global profession "Software Engineer." The "IT" category, which also includes "Network Administrator" and "Help Desk Technician," remains unchanged.	No change.	No change.
Category becomes empty after merge	Category is removed unless it has direct identity links. If identity links exist, the category is preserved.	No change. The empty category is retained.	"Interns" category when all intern positions are merged	All local professions within the "Interns" category are merged with global professions. If the "Interns" category has no direct identity links (e.g., no employees are directly associated with the category), the category is removed. If there are direct identity links, the category is preserved.	Empty or unneeded categories contribute to taxonomy inefficiency	Clean and organize category, or leave as is.

8. Identity Connection Handling: Maximizing Accuracy and Minimizing Disruption

Scenario	What Happens	Example	Edge Case Handling	Business Rule
Person has local profession only	Connection is transferred to the corresponding global profession. The link to the local profession is removed.	Jane's connection to the local profession "Data Analyst" is moved to the global equivalent "Data Analyst."	If no global match exists, the local profession may be kept, and the identity link will remain unchanged. A notification is generated for manual review.	Ensure correct global title is in place. Acknowledge the notification.
Person has both local and global versions	The local connection is removed, and the global connection is kept. This simplifies duplicate connections.	A person has duplicate connections to both the local and global versions of "Project Manager." The local connection is removed, and only the global connection is retained.	The system detects and automatically resolves this duplication. A log entry is created.	Ensure only one title and role. Audit the log.
Person has multiple local professions	Each connection is transferred to the appropriate global profession independently.	John has connections to 3 local roles, and each role has a matching global profession. Each connection is updated accordingly.	Each profession is processed independently to ensure that all relevant identity links are updated. A summary report is generated.	Ensure roles are connected to global. Validate the report.
Person has a global profession that matches another	Both global profession links are preserved unless deliberately merging (see Section 12). A warning is displayed.	A person has connections to both "Software Developer" and "Programmer," which are distinct global professions. Both links are kept unless a direct merge operation is initiated.	Only direct merge operations affect global-to-global links. A policy forbids this action.	Do not merge without explicit approval.
Person has professions with direct category links	Category links are preserved during profession merging. Special relationships with categories are maintained.	A department head has a direct association with the "Management" category. This association is maintained even after the department head's profession is merged.	Special category relationships are maintained separately using a dedicated relationship management module.	Category relationships are preserved to ensure business process continuity.
Multiple people share the same local profession	All connections are transferred to the same global profession consistently.	A team of 8 "Support Specialists" are all reconnected to the global role "Technical Support Specialist."	A bulk update handles all identities consistently, ensuring that all members of the team are correctly associated with the updated profession.	Ensure correct update occurs. A separate validation report is generated for each team.
Profession has no associated identities	The profession is merged or deleted with no identity updates needed.	Legacy job titles that are no longer in use are merged or deleted without affecting any identity connections.	The system handles "orphaned" professions normally. This action is logged for auditing.	No updates required. No employee is touched.