HR-Analytics.pptx gi to home and enjoy the human res

food

1. HR Analytics: Welcome! We will explore HR analytics and how to make better decisions using data. by Ajinkya Sarage

2. Objectives of HR Analytics Improve Performance Boost employee performance through data-driven strategies. Reduce Costs Optimize workforce costs by identifying inefficiencies. Increase Retention Uncover factors affecting retention and take proactive steps.

3. The Importance of Data-Driven Decision Making 1 Evidence-Based Reduce bias and subjectivity, fostering trust and transparency. 2 Actionable Insights Gain actionable insights from data to drive positive change. 3 Strategic Advantage Gain a competitive advantage by making informed decisions.

4. Key HR Analytics Metrics and KPIs Employee Turnover Tracking the rate of employee departures Employee Engagement Measuring employee satisfaction and motivation Recruitment Efficiency Analyzing the time and cost of hiring processes Training Effectiveness Assessing the impact of training programs on skills.

5. Tools Used in HR Analytics Spreadsheets Data organization and basic analysis Data Visualization Tools Create meaningful and compelling visuals Business Intelligence Software Advanced reporting and analytics capabilities Machine Learning Algorithms Predictive analytics and automation

6. Application of Data Analytics 1 Talent Acquisition: identify ideal candidates and predict performance. 2 Performance Management: optimize performance reviews and development plans. 3 Compensation and Benefits: analyze salary and benefits data to attract and retain top talent. 4 Employee Engagement: understand employee satisfaction and implement proactive measures.

7. Challenges in Implementing HR Analytics Data Quality Ensuring accurate and reliable data is crucial. Data Security Protecting employee data is of paramount importance. Organizational Resistance Overcoming resistance to change is essential. Skills Gap Developing skills and expertise in HR analytics is critical.

8. Future of HR Analytics 1 AI and Automation Automating tasks and enhancing decision-making. 2 Predictive Analytics Forecasting talent needs and optimizing strategies. 3 Data Visualization Creating interactive and insightful dashboards.

9. Conclusion 1 Data-Driven Decisions Harness the power of data to drive informed decisions. 2 Strategic Advantage Gain a competitive edge in the talent landscape. 3 Continuous Improvement Embrace a culture of data-driven learning and growth.

10. Data Visualization and Reporting 1 Clear and Concise Present data in an easy-to-understand manner. 2 Interactive Dashboards Enable user exploration and insights. 3 Actionable Reports Provide clear recommendations for improvement.