CASE STUDY ON Human resource analyticesR782024.pptx

CASE STUDY ON Human resource analyticesR782024.pptx

1. CASE STUDY ON HR ANALYTICS Dr Nagarajan G Professor – MBA Rajarajeswari College of Engineering Bengalurue-74

2. A case study is a detailed analysis of a specific situation, individual, group, or phenomenon. It's an in-depth examination of a real-life scenario, often used in research, education, and business to: 1. Explore complex issues 2. Identify patterns and relationships 3. Develop theories or hypotheses 4. Test concepts or models 5. Provide insights and recommendations

3. Case studies typically involve: 1. Data collection (interviews, observations, documents, etc.) 2. Data analysis (identifying themes, patterns, etc.) 3. Interpretation of findings 4. Drawing conclusions and making recommendations

4. CASE STUDY ON HR HCL company , a large retail chain with 10,000 employees Problem: High employee turnover rate (30% annually), leading to increased recruitment and training costs Objective: Use HR Analytics to identify the root causes of employee turnover and develop strategies to reduce it.

5. Data Collection Employee data (demographics, job title, tenure, salary, performance ratings) Turnover data (reasons for leaving, exit interview feedback) HR metrics (training participation, engagement survey results)

6. Data Analysis Descriptive analytics: Identified top reasons for turnover (lack of career growth, poor management, unsatisfying work environment) Inferential analytics: Found correlations between turnover and factors like job satisfaction, engagement, and manager quality Predictive analytics: Developed a model to predict employee turnover based on variables like tenure, performance, and training participation

7. Solutions Career Development Programs: Implemented training and development initiatives to address lack of career growth Manager Training: Provided training for managers to improve leadership skills and address poor management issues Work Environment Improvements: Made changes to work environment to address unsatisfying work conditions Employee Engagement Initiatives & Recognition and Rewards: Implemented recognition and rewards programs to boost employee satisfaction and commitment. Predictive Modeling: B uilt a model to predict turnover risk based on employee characteristics and behaviors.

8. Prescriptive analytics in HR analytics can be achieved through various techniques, including: 1. Machine Learning 2. Artificial Intelligence 3. Simulation Modeling 4. Optimization Algorithms 5. Decision Trees The benefits of prescriptive analytics in HR analytics include: 1. Data-driven decision making 2. Improved HR outcomes 3. Increased efficiency 4. Enhanced employee experience 5. Better talent management Prescriptive analytics in HR analytics

9. Results:- Turnover rates decreased by 25% within 6 months. Employee satisfaction and engagement improved by 15%. Recruitment and training costs reduced by 20%. Improved employee satisfaction and engagement scores Lessons learned from the case Data-driven insights can inform effective HR strategies. Addressing root causes of turnover can lead to significant retention improvements. Continuous monitoring and evaluation are crucial to sustaining results.