Certified Human Resources Analyst
This interactive workshop follows several practical learning methods that enable participants to immediately apply all the tools acquired during the workshop. The workshop covers various case studies and professional practices adopted from top global companies. It also includes exercises and activities that focus on enhancing the analytical skills of the participants. Additionally, it relies on methods to change professional beliefs, thereby reinforcing participants’ conviction about the significant importance of data analysis in all aspects of human resources practices. The data analysis program used is SPSS.
By the end of the course, participants will be able to:
- Demonstrate a deep understanding of the uses of data analysis in various HR departments.
- Apply data analysis tools to improve recruitment and selection decisions and predict attrition rates.
- Analyze the impact of education and development programs on employee motivation using linear regression modeling.
- Utilize statistical tests to promote a culture of diversity and inclusion in the organization.
- Predict employee performance levels extracted from employee engagement survey data.
- Apply tools and strategies for analyzing HR data within their own work environment.
This training course targets all professionals specialized in various HR fields, such as training and development, talent management, organizational development, workforce planning, performance and rewards, as well as HR business partners and professionals in general.
- Data-driven HR analytics
- Defining HR analytics
- The analytics process: Using data to influence business decisions
- Information sources: HR data is not limited to the HR department
- Most commonly used HR information systems and programs
- Basic statistics
- Types of variables
- Statistical significance
- Descriptive data vs. data analysis
- Modeling and predictive analysis
- How data can contribute to HR job design and enrichment
- HR professionals and data synergy: Importance of alignment for business interests
Analyzing Recruitment Data and Predicting Employee Attrition Rates
- Dependent and independent variables
- Categorical and continuous variables
- Logistic regression methodology: Building predictive models
- Reducing guesswork in hiring decisions: Relying on data when selecting candidates
- Validating the effectiveness and reliability of candidate selection methods
- Predicting rejection and filtering candidate lists
- Predicting employee attrition rates in your organization
Data-driven Approach in Education and Development: Impact of Training Programs on Employee Motivation
- Transforming survey responses into continuous data for expanded analysis opportunities
- Survey design: Checking internal consistency with Cronbach’s alpha coefficient
- Removing irrelevant responses from the survey (outliers)
- Verifying data representativeness using normality tests
- Understanding the relationship between business variables using Pearson correlation coefficient
- Using linear regression analysis to examine the impact of training programs on employee motivation
- Simulating an alternative model to Kirkpatrick’s model for evaluating training impact
In-depth Analysis of Diversity and Inclusion Initiatives in the Organization
- Importance of diversity and inclusion (racial and gender) in organizations
- Pitfalls in using descriptive data to showcase institutional bias
- Statistical significance (p-value) and levels of freedom
- t-tests and chi-square tests: Simple mathematical formulas
- Analyzing gender bias (male/female) in the workforce and job positions using frequency tables and chi-square
- Exploring racial diversity among workgroups using descriptive statistics
- Using t-tests to report biased promotions for a specific gender
- Multiple regression analysis to model and predict racial diversity variations in workgroups
Exploring the Relationships between Employee Performance, Engagement, and Organizational Profitability
- Measuring employee engagement rates
- Factor analysis to check questionnaire reliability in employee engagement surveys
- Data analysis to explore the relationship between customer loyalty and employee engagement rates
- Multiple stepwise regression: An effective tool for exploring the relationship between different business.