CASE STUDY ON CASE STUDY ON HR782024.pptx
- 1. CASE STUDY ON BUSINESS DECISIONS USING DATA Dr Nagarajan G Professor – MBA Madanapalle Intitute of Technology and Science
- 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 employee analytics: Developed a model turnover based on variables to predict 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: Built 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: 6. Data-driven decision making 7. Improved HR outcomes 8. Increased efficiency 9. Enhanced employee experience 10.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 1. Data-driven insights can inform effective HR strategies. 2. Addressing root causes of turnover can lead to significant retention improvements. 3. Continuous monitoring and evaluation are crucial to sustaining results.