IIM Nagpur – Post Graduate Certificate Programme for Advanced Strategic HR and Analytics

Imagine stepping into the shoes of an HR leader at a thriving company. Each day, you're faced with crucial decisions that impact your organisation's most valuable asset: its people. How do you identify top talent, predict employee turnover, and boost overall productivity? The answer lies in Advanced Strategic HR & Analytics.

By enrolling in our Advanced Strategic HR & Analytics, you embark on a transformative journey where data becomes your most powerful ally. Here’s how the programme will help you transform:

• Context setting for Data-Driven Strategic HR:
  • Understanding Strategic Goals: Explore how business objectives influence
  • HR priorities and decisions.
  • Creating Data-Driven Metrics: Develop HR metrics aligned with organizational strategy using insights from business models.
  • Data-Driven HR Decision Making: Apply analytical tools to assess and support strategic HR choices and strategic organization goals
  • Navigating Emerging HR Challenges: Address contemporary workforce challenges, ensuring HR strategies remain adaptive to evolving business
    needs.
• New Age Strategic HRM practices across Sectors:
  • Exploring Sector-Specific HR Trends: Investigate how various industries leverage data to enhance employee management.
  • Customizing HR Metrics by Industry: Identify critical HR metrics tailored to specific industries like technology, finance, and manufacturing, and their role in strategic decision-making.
  • Sector-Specific HR Challenges: Understand the unique HR challenges across different sectors and explore data-driven strategies to address these challenges effectively.
• HR-Driven Strategic Transformation
  • Data-Driven Transformation Frameworks: Design frameworks that use data insights to lead strategic organizational changes.
  • Aligning Organizational and Individual Goals: Focus on aligning company-wide objectives with team and individual targets for cohesive performance.
  • HR as a Catalyst for Strategic Change: Position HR as a critical enabler of business turnarounds, using HR strategies to drive transformational outcomes.
• Introduction to HR Analytics
  • Understand the domain of HR analytics and its application in modern organizations.
  • Aligning HR Analytics to Organizational Goals, Objectives and HR Strategy
  • Explore the HR analytics continuum and its impact on decision-making.
  • Understand the basics of Analytics and various tools used
    Learn to design and implement HR analytics projects using evolving HR technologies.
  • Challenges in implementing HR Analytics
• Descriptive Analytics and Data Cleaning
  • Identify sources of HR Data
  • Capture relevant HR data from various sources and clean the data for analysis.
  • Analyze HR metrics to measure organizational performance and effectiveness.
  • Develop customized HR metrics tailored to organizational needs.
  • Utilize data visualization techniques to communicate HR insights effectively.
  • Implement data governance practices to ensure data quality and integrity.
  • Explore emerging trends in HR analytics and their implications for data management.
  • Case studies and practical exercises on HR data analysis and interpretation
• Predictive Analytics and Modelling
  • Choose appropriate predictive analytic models for quantitative HR data.
  • Work with qualitative HR data and interpret predictive analytic results.
  • Implement machine learning algorithms and AI for HR prediction tasks, such as employee turnover or performance forecasting.
  • Evaluate the accuracy and performance of predictive models using metrics such as precision, recall, and ROC curves.
  • Incorporate time-series analysis techniques to forecast HR trends and patterns.
• Prescriptive Analytics and Optimization
  • Apply prescriptive analytics techniques to address HR challenges and optimise processes.
  • Customise solutions based on contextual requirements and stakeholder needs.
  • Implement decision support systems to facilitate data-driven decision-making in HR.
  • Utilize simulation modelling to predict the impact of HR policies and interventions.
• Workforce planning, Talent Acquisition and Development Analytics
  • Utilise analytics to improve workforce planning, talent acquisition processes and strategies.
  • Analyse employee development data to identify skill gaps and training needs.
  • Predictive Analytics using NLP
  • Develop strategies for talent development and succession planning.
• Performance Management and Rewards Analytics
  • Analyse employee performance and potential using predictive analytics models.
  • Employee Engagement Surveys with NLP Sentiment Analysis
  • Understand the relationship between performance, potential, and rewards.
  • Design and implement performance management systems based on analytics insights.
• Employee Engagement and Retention Analytics
  • Measure and track employee engagement levels using analytics tools.
  • Identify factors influencing employee engagement and satisfaction.
  • Develop strategies to enhance talent engagement and retention.
  • Utilize predictive modelling to forecast employee turnover and attrition rates.
  • Implement employee feedback mechanisms for continuous improvement of engagement initiatives.
• Culture Fit and Organisational Wellness Analytics
  • Assess value congruence between organisational culture and employee values.
  • Analyse induction processes to ensure cultural alignment and employee engagement.
  • Analyse employee wellness data to identify trends and patterns.
  • Implement strategies for fostering diversity and inclusion within the organizational culture.
  • Utilize sentiment analysis techniques to gauge employee perceptions of organizational culture.
• Introduction to R for HR Analytics
  • Overview of R programming language
  • Data manipulation and analysis with R
  • Statistical analysis and visualization in HR analytics using R
  • Explore machine learning and AI techniques for predictive HR analytics using R.
  • Apply R packages specific to HR analytics
• Capstone Project
  • Apply learned concepts and techniques to a real-world HR analytics project.
  • Collect, analyse, and interpret HR data using Python, R, and advanced Excel
  • Develop recommendations for improving HR processes and practices.
  • Present findings and insights using Power BI and Tableau.