HR professionals today have access to more data than ever before. However, data itself is of no use without any insights. Using analytics HR professionals will be able to derive insights by measuring the data collected and draw meaningful inferences to drive business decisions. This is a shift from traditional models to a more evidence-driven HR. It has also become a requirement for HR professionals to focus on being a proponent of employee experience as a more scientific and data-based process.
HR Analytics is quickly becoming a vital part of effective HR strategies. By utilizing analytics to look into patterns in all available data, HR professionals will be able to discover important connections that will allow them to become more effective at hiring and retaining the right talent. Such data will also help talent learn and grow within the organisation.
HR Analytics also allow organizations to predict future needs and how to utilize the talent opportunities available adapting to rapid changing business needs. Workforce and organization quality increases as HR professionals can conduct more effective studies on whether to filling an empty position or on-boarding a new employee. With organisations moving away from traditional HR model, and analytics shaping the workforce of the future, HR professionals are expected to have a deep understanding on HR Analytics to stay relevant.
Course Information
- Duration: 1 Day / 8 Hours
- Certification:Participants will be awarded a Certificate of Completion upon completing the course
- Who Should Attend: HR Professionals, HR Generalist, Business Leaders, Senior Executives and Anyone interested in acquiring the essential knowledge on how to use HR Analytics to make better people and organization decisions
Course Objective
Pre-Requisite
Examination
Module 1
What Is Analytics?
- Analytics Capabilities
- Analytics Value Chain
- Analytics Model
Module 2
How Human Capital Analytics Is Being Used
- HR Analytics Maturity Model
- Types of analysis
- Workforce Analytics
- Employee Engagement Analysis
- Employee Satisfaction Survey Analysis
- Channel/Vendor Optimization
- Succession planning
- Retention /attrition
- Recruitment process
- Sources of data
- Various approaches for turning data into information
- Value Paths for Analytics projects
Module 3
Financial Connections
- Focusing on the Purpose
- Working with Consultants and Coaches
- Designing and Delivering Reports
- Making an Impact
- Process Management
Module 4
Data Issues
- Efficiency Measures
- Effectiveness Measures
- Business Outcome Measures
Module 6
Fundamentals in Predictive Analytics
- Variable selection method
- Pre requisite to Predictive Modelling
- Fitting a Model to Data
- Simple linear regression
- Interpretation of Results
- Assumptions Validations
- Introduction to Multiple regression analysis, Stepwise regression
Module 5
Predictive Statistics Examples
- Begin with the End in Mind
- Go Back to the Beginning
- Who Owns Data, and Will They Share It?
- What Will You Do with the Data?
- What Form Is the Data In?
- Is the Data Quality Sufficient?
Module 6
Predictive Analytics in Action
- First Step: Determine the Key Performance Indicators
- Second Step: Analyze and Report the Data
- Relationships, Optimization, and Predictive Analytics
- Predictive Analytics
- Interpreting the Results
