Employee Success Analytics — Workforce & Retention Insights (NextGen Corp)

Data-driven insights into workforce performance, turnover patterns, and compensation fairness

📋 Project Objectives

Analyse employee retention and turnover trends across departments
Evaluate performance distribution by role and team
Assess salary structures relative to performance
Identify high-risk employees and departments
Provide evidence-based recommendations to improve retention and engagement

🎯 Problem Statement

The organisation lacked clarity on:

• Which departments faced higher turnover risk
• How employee performance related to compensation
• Why employees were leaving and how retention could be improved

PostgreSQL SQL Excel KPI Reporting

📊 Data Description

Designed and implemented the 'NextGen' database in PostgreSQL to analyse employee turnover trends, identify root causes of high turnover rates by department, and predict employee attrition risk. The database consisted of:

Employees Table: Essential employee details like name, job title, hire date, salary, performance score, attendance rate, and department affiliation

Departments Table: List of departments within NextGen Corp. (e.g., Engineering, Sales, HR, Marketing)

Performance Table: Tracks monthly performance scores of employees, allowing analysis of performance trends over time

Attendance Table: Tracks attendance records for employees, including whether they were present or absent

Turnover Table: Contains data on employees who left the company, including the reason for leaving

Salaries Table: Provides salary data, including historical salary changes for each employee

🛠️ Tools & Techniques

PostgreSQL: Database design, complex queries, relational data analysis

SQL: Data extraction, aggregation, performance calculations

Excel: Data validation and exploratory analysis

🔍 Analysis Performed

• Department-level turnover rate analysis
• Performance score distribution and risk identification
• Salary vs performance correlation analysis
• Retention pattern analysis across roles and tenure
• Exit reason categorisation and trend evaluation

1️⃣ Performance by Department

• Marketing and Engineering departments showed the highest average performance scores (4.13 and 4.10 respectively)
• Sales had the lowest average performance and fewer top-performing employees
• 45 employees had performance scores below 3.5, indicating potential retention risk

2️⃣ Exit Reasons & Retention Drivers

• Career development and professional growth were major drivers of employee exits
• Departments with higher performance tended to offer higher average compensation

🎯 Recommendations

1. Introduce Structured Career Development and Mentorship Programmes

Create clear career pathways and mentorship opportunities to address professional growth concerns.

2. Implement Targeted Performance Coaching for At-Risk Employees

Focus on the 45 employees with performance scores below 3.5 to improve retention.

3. Review Compensation Equity Across Departments

Ensure salary structures align with performance and market standards.

4. Strengthen Recognition and Feedback Mechanisms

Implement regular performance reviews and recognition programmes.

5. Conduct Structured Exit Interviews to Improve Retention Strategies

Gather systematic feedback to understand and address root causes of turnover.

📈 Outcome

Produced interactive dashboards and workforce performance reports that enabled HR leadership to:

Identify retention risks

Optimise compensation strategies

Improve employee engagement

Enhanced workforce planning

✨ Skills Demonstrated

HR Analytics & Workforce Planning Database Design & SQL Queries Statistical Analysis & Modeling Cohort & Retention Analysis Data-Driven HR Strategy

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