Traditional workforce planning relies on subjective assessments. SkillNet Analytics changes that.
By integrating Skills Network Analysis, Organizational Network Analysis, and psychometric testing, SkillNet Analytics delivers deep, objective insights into workforce capabilities — identifying high-potential employees, recognizing transferable skills, and ensuring the right people are placed in the right roles.
1. Skills Network Analysis (SNA)
Objective: Map and measure the relationships and interdependencies between various skills within the organization.
Method: Create a co-occurrence matrix and network graph to visualize skill interconnections.
| Metric | What it measures |
|---|---|
| Degree Centrality | Number of direct connections a skill has — indicates a highly interconnected skill |
| Betweenness Centrality | How often a skill lies on the shortest path between others — acts as a bridge skill |
| Closeness Centrality | How close a skill is to all other skills in the network |
| Eigenvector Centrality | Influence of a skill — considering not just connections but their importance |
2. Organizational Network Analysis (ONA)
Objective: Understand the distribution and connectivity of skills across the organization.
Method: Utilize centrality metrics to identify critical skills and their influence within the network — revealing which skills are concentrated, which are distributed, and where gaps exist.
3. Psychometric Testing
Objective: Assess cognitive abilities, personality traits, and behavioral tendencies.
Examples: McQuaig System, MBTI, Hogan Assessments, DISC Profile.
| Metric | What it measures |
|---|---|
| Dominance (D) | Assertiveness, control, and desire for power — drive to lead and make decisions |
| Sociability (S) | Need for social interaction — preference for engaging and persuading others |
| Relaxation (R) | Stress tolerance, patience, and steadiness under pressure |
| Compliance (C) | Adherence to rules, attention to detail, and accuracy |
| Mental Agility | Cognitive ability — problem-solving speed, logical reasoning, analytical strength |
Composite Scoring
Each employee receives a composite score combining SNA metrics and psychometric results. This score is compared against the ideal profile for a target role. The employee with the lowest variance from the ideal score is identified as the best fit — removing subjectivity from talent decisions.
Leadership Role Profile
| Dimension | Ideal Score |
|---|---|
| Leadership | 90 |
| Communication | 85 |
| Problem Solving | 80 |
| Degree Centrality | 0.85 |
| Dominance (D) | 85 |
| Mental Agility | 85 |
IT Role Profile
| Dimension | Ideal Score |
|---|---|
| Python | 85 |
| Java | 80 |
| SQL | 80 |
| Degree Centrality | 0.85 |
| Compliance (C) | 85 |
| Mental Agility | 85 |
Enhanced Decision-Making
Data-driven insights improve the accuracy and objectivity of workforce planning decisions — removing bias and gut instinct from talent selection.
Identifying High Potential
Recognizes and nurtures talent by aligning individuals with suitable roles and promoting internal growth through objective skill mapping.
Promoting Internal Mobility
Leverages transferable skills within the organization — supporting employee development and career progression without external hiring costs.
Reducing Turnover
Increases employee engagement and retention by ensuring the right fit for roles — reducing the financial and cultural cost of misplacement.
Optimizing Recruitment
Identifies the best candidates for specific roles based on a comprehensive analysis of skills, network centrality, and psychometric data.
Supporting Succession Planning
Provides a clear, data-driven view of internal talent that can be developed for future leadership roles — reducing succession risk across the enterprise.
Leadership Role — Results
| Employee | Composite Score | Variance from Ideal | Fit |
|---|---|---|---|
| Employee 5 | 87.17 | 2.83 | Best Fit |
| Employee 2 | 85.67 | 4.33 | Strong Candidate |
Employee 5 scores highest on leadership composite with the lowest variance from the ideal profile — making them the objective best fit for the leadership role.
IT Role — Results
| Employee | Composite Score | Variance from Ideal | Fit |
|---|---|---|---|
| Employee 2 | 85.14 | 0.14 | Best Fit |
| Employee 5 | 85.57 | 0.57 | Strong Candidate |
Employee 2 emerges as the best fit for the IT role with the lowest variance — demonstrating how the same talent pool can be objectively evaluated across different role requirements.
Key Insight
By integrating Skills Network Analysis, Organizational Network Analysis, and psychometric testing, SkillNet Analytics ensures the right people are placed in the right roles — optimizing talent management and driving organizational success through data, not intuition.