Category Management
Category Management maintains the master list of role categories, sub-categories, and sub-sub-categories.It supports unlimited levels to organize job roles clearly across the RMS. Used by JD Creation, Candidate Profiles, and Profile Articulation.
Fields
| Field | Type | Description |
|---|---|---|
| name | String | Category name (e.g., “Health & Safety”, “Engineering”) |
| status | String | "active" or "inactive" |
| description | String | High-level description of what this category covers |
| subCategories | Array<SubCategory> | List of Sub Categories |
| ddimMetadata | DDIMMetadata | Mapping to DDIM-AI framework for interviews, competency assessment, and knowledge universe |
Sub Category Model
This now includes role purpose, responsibilities, coverage, standards, KPIs, competencies, and DDIM-AI knowledge levels.| Field | Type | Description |
|---|---|---|
| name | String | Sub Category name (e.g., “HSE Officer”) |
| description | String | Description of the role cluster |
| totalExperience | String | Required experience (e.g., “2–5 years”) |
| primaryObjective | String | The main purpose of this subcategory role |
| coreResponsibilities | Array<String> | Key responsibilities |
| coverageAreas | Array<String> | Areas like Excavation, Confined Space, etc. |
| interfaces | Array<String> | Stakeholder interactions |
| competenceRequirements | Array<String> | DDIM / domain competences |
| preferredCertifications | Array<String> | NEBOSH, IOSH, OSHA, etc. |
| keyStandards | Array<String> | ISO 45001, OSHA 1910, NFPA, etc. |
| kpis | Array<String> | Performance KPIs |
| subSubCategories | Array<SubSubCategory> | Nested specialization |
| knowledgeUniverse | KnowledgeUniverse | DDIM-AI structured question bank (Levels 1–5) |
| behavioralMatrix | Array<BehavioralCompetency> | DDIM-AI C1–C15 behavioral competencies |
Sub Sub Category Model
| Field | Type | Description |
|---|---|---|
| name | String | Specialization name (e.g., “Consulting”, “Contracting”) |
| description | String | Description |
| totalExperience | String | Required experience |
| targetCompanies | Array<String> | Linked companies |
| ddimTags | Array<String> | Optional DDIM domains (e.g., PTW, CSE, Process Safety) |
DDIM-AI Knowledge Universe Model
| Field | Type | Descriptio |
|---|---|---|
| level1 | Array<Question> | Fundamentals (Conceptual) |
| level2 | Array<Question> | Applied & Scenarios (Operational) |
| level3 | Array<Question> | Expert Q&A (Root Cause / Diagnostics) |
| level4 | Array<Question> | Expert & Case-Based (Real incidents) |
| level5 | Array<BehavioralQuestion> | Behavioral Competency Matrix (C1–C15) |
Purpose
Category Management defines the complete multi-level role taxonomy used across the RMS.It enables administrators to structure roles into Category → Sub Category → Sub Sub Category, along with detailed role attributes such as objectives, responsibilities, competencies, standards, certifications, and KPIs. With the integration of the DDIM-AI Knowledge Universe, Category Management also becomes the central source of truth for:
- Role-based knowledge mapping (Levels 1–5)
- Scenario, diagnostic, and expert-level safety/functional Q&A
- Behavioral competency evaluation (C1–C15)
- Automated JD creation and candidate evaluation
- AI-driven profile articulation and interviewing workflows
Summary
Category Management forms the core master structure of the RMS.It organizes roles into multi-level hierarchies, ensures consistency in naming, enables accurate job role definition, and supports advanced AI-based evaluation. Each Category contains Sub Categories and Sub Sub Categories, with detailed definitions such as:
- Role purpose & objective
- Core responsibilities
- Safety or functional coverage areas
- Interfaces & stakeholder mapping
- Competence & certification requirements
- Applicable standards and KPIs
- DDIM-AI knowledge universe (Levels 1–5)
- Behavioral competency matrix (C1–C15)
- JD Creation
- Candidate Profile Structuring
- Profile Articulation
- Interview Q&A Generation
- Assessment & Training Readiness Analysis