7 Topics
5 Days
Programme Overview
Training Description
- HR directors and managers
- Employee engagement specialists
- HR business partners
- People analytics professionals
- Talent management and development leaders
- Organizational development specialists
- Data analysts in HR
- Team leaders and supervisors
- Communications and public relations professionals
- Senior executives and operations managers
Session Objectives
- Understand the strategic link between employee engagement and business outcomes.
- Master the use of Business Intelligence tools for HR data analysis.
- Develop a data-driven framework for an employee engagement strategy.
- Identify key drivers of engagement using quantitative and qualitative data.
About the Course
In today’s competitive talent landscape, relying on intuition alone is no longer sufficient to build a motivated workforce or retain key personnel. Our BI Tools for Driving Employee Engagement Training Course bridges the gap between traditional human resources and modern data science by equipping HR professionals and business leaders with the technical skills to build targeted, evidence-based engagement strategies. Guided by people analytics specialists, participants will master the application of Business Intelligence tools to synthesize complex workforce data—including engagement surveys, productivity metrics, and turnover rates—into clear visual dashboards. By combining quantitative risk modeling with hands-on case exercises, this program prepares HR leads to uncover hidden sentiment patterns, calculate turnover probability, demonstrate clear ROI on talent initiatives, and transform human resources into a proactive strategic powerhouse.
Curriculum & Topics
7 Topics | 5 Days
-
Subtopic 1.1:
The business case for investing in employee engagement.
-
Subtopic 1.2:
The difference between engagement, satisfaction, and happiness.
-
Subtopic 1.3:
The employee lifecycle and key moments that matter.
-
Subtopic 1.4:
Understanding key metrics for measuring engagement.
-
Subtopic 1.5:
Linking engagement data to business performance.
-
Subtopic 2.1:
An overview of popular Business Intelligence tools (e.g., Power BI, Tableau).
-
Subtopic 2.2:
The process of collecting and cleaning HR data.
-
Subtopic 2.3:
Integrating data from various sources (surveys, HRIS, performance reviews).
-
Subtopic 2.4:
Foundational data visualization principles.
-
Subtopic 2.5:
Ensuring data integrity and governance.
-
Subtopic 3.1:
Conducting descriptive analysis of engagement survey data.
-
Subtopic 3.2:
Using BI tools to create interactive dashboards and reports.
-
Subtopic 3.3:
Segmenting engagement data by demographics, department, and tenure.
-
Subtopic 3.4:
Identifying trends and patterns in employee feedback.
-
Subtopic 3.5:
Using statistical analysis to validate findings.
-
Subtopic 4.1:
The difference between leading and lagging indicators.
-
Subtopic 4.2:
Conducting correlation and regression analysis to identify key drivers.
-
Subtopic 4.3:
Using qualitative data (e.g., open-ended feedback) to add context.
-
Subtopic 4.4:
Creating a driver-impact matrix to prioritize interventions.
-
Subtopic 4.5:
Linking engagement drivers to specific business goals.
-
Subtopic 5.1:
Developing targeted initiatives based on data insights.
-
Subtopic 5.2:
Creating a roadmap for implementing engagement programs.
-
Subtopic 5.3:
Best practices for communicating changes to employees.
-
Subtopic 5.4:
The role of pulse surveys in a continuous listening strategy.
-
Subtopic 6.1:
The art of storytelling with data to influence leadership.
-
Subtopic 6.2:
Creating clear and compelling presentations for executives.
-
Subtopic 6.3:
Presenting insights and recommendations in a business-centric way.
-
Subtopic 6.4:
Building a business case for engagement initiatives with ROI.
-
Subtopic 6.5:
Fostering a culture of data literacy within the HR team.
-
Subtopic 7.1:
Emerging trends in employee listening and feedback technology.
-
Subtopic 7.2:
The role of predictive analytics in forecasting turnover and burnout.
-
Subtopic 7.3:
Using AI and natural language processing for sentiment analysis.
-
Subtopic 7.4:
The ethical considerations of AI in employee monitoring.
-
Subtopic 7.5:
A personal action plan for future-proofing your engagement strategy.
