Duration 3 days – 21 hrs
Overview
This course equips HR professionals with practical skills to collect, analyze, interpret, and communicate workforce data effectively. Participants will learn how to transform HR metrics into meaningful insights, create clear visualizations, and develop data-driven stories that support management decisions.
The course uses common HR scenarios involving recruitment, employee turnover, absenteeism, performance, engagement, learning and development, diversity, and workforce planning. Practical exercises may be completed using Microsoft Excel and PowerPoint. Power BI may be introduced as an optional visualization tool.
Objectives
- Explain the role of data analysis in strategic and operational HR decision-making.
- Identify relevant HR metrics and key performance indicators.
- Collect, organize, clean, and validate HR data.
- Apply descriptive analysis to common HR concerns.
- Interpret trends, patterns, relationships, and workforce indicators.
- Select appropriate charts and visualizations for different types of HR data.
- Design clear HR reports, dashboards, and executive summaries.
- Transform analytical findings into structured and compelling data stories.
- Present evidence-based HR recommendations to management and stakeholders.
- Recognize privacy, confidentiality, ethics, and bias considerations in people analytics.
Target Audience
- HR managers and supervisors
- HR business partners
- HR officers and specialists
- Recruitment and talent acquisition professionals
- Learning and development professionals
- Compensation and benefits personnel
- Employee relations and engagement professionals
- Workforce planning and organizational development teams
- HR reporting and HRIS personnel
- Professionals responsible for preparing workforce reports and presentations
Prerequisites
- Basic knowledge of HR processes and terminology
- Basic proficiency in Microsoft Excel
- Basic experience preparing reports or presentations
- A laptop with Microsoft Excel and PowerPoint installed
- No programming, statistics, or advanced analytics experience is required.
Course Outline
Day 1 – HR Data and Analysis Fundamentals
Module 1: Introduction to HR Data Analytics
- What HR analytics is and why it matters
- Moving from administrative reporting to strategic insights
- Descriptive, diagnostic, predictive, and prescriptive analytics
- Questions that HR data can help answer
- The HR analytics process
- Common challenges in using workforce data
Module 2: HR Metrics and Key Performance Indicators
- Difference between data, metrics, KPIs, and insights
- Selecting metrics aligned with business and HR objectives
- Common HR indicators:
- Headcount and workforce composition
- Recruitment efficiency
- Time-to-fill and cost-per-hire
- Employee turnover and retention
- Absenteeism
- Learning effectiveness
- Employee performance
- Engagement and satisfaction
- Diversity and inclusion
- Leading and lagging indicators
- Avoiding vanity metrics and information overload
- Creating an HR measurement framework
Module 3: Preparing HR Data for Analysis
- Identifying internal and external HR data sources
- Understanding structured and unstructured HR data
- Organizing HR data in a usable format
- Removing duplicates and correcting inconsistencies
- Handling missing and incomplete information
- Standardizing dates, categories, and employee records
- Data validation and quality checks
- Protecting confidential and sensitive employee information
Module 4: Essential Excel Techniques for HR Analysis
- Using Excel tables, filters, and sorting
- Applying essential formulas and functions
- Conditional calculations and lookups
- Using PivotTables and PivotCharts
- Creating calculated HR metrics
- Summarizing information by department, position, location, or period
Practical Exercise: Clean and summarize a sample employee dataset and calculate selected HR metrics.
Day 2 – Analyzing and Visualizing HR Data
Module 5: Descriptive Analysis for HR
- Understanding totals, percentages, rates, averages, and distributions
- Comparing groups and workforce segments
- Trend and period-over-period analysis
- Identifying patterns, changes, and anomalies
- Segmenting data by department, tenure, role, age group, or location
- Distinguishing correlation from causation
- Avoiding misleading conclusions
Module 6: Applying Analysis to Common HR Concerns
- Recruitment funnel analysis
- Turnover and retention analysis
- Absenteeism analysis
- Employee performance analysis
- Training participation and effectiveness
- Engagement survey analysis
- Workforce diversity analysis
- Workforce capacity and planning
- Converting HR questions into analytical questions
Case Activity: Analyze a workforce issue and identify its possible contributing factors.
Module 7: Principles of HR Data Visualization
- Purpose of data visualization
- Matching chart types to analytical questions
- Using bar, line, column, pie, scatter, and combination charts
- Showing comparisons, trends, composition, and relationships
- Applying appropriate titles, labels, colors, and annotations
- Reducing clutter and unnecessary decoration
- Designing accessible and management-friendly visuals
- Common charting mistakes and misleading presentations
Module 8: Designing HR Dashboards and Reports
- Identifying the dashboard’s purpose and audience
- Selecting the most important KPIs
- Organizing dashboard information logically
- Using filters and categories effectively
- Creating executive, operational, and analytical views
- Highlighting exceptions and areas requiring action
- Introduction to Excel dashboards
- Optional introduction to Power BI for HR reporting
Practical Exercise: Create a one-page HR dashboard using a sample dataset.
Day 3 – Data Storytelling and Presentation
Module 9: Fundamentals of Data Storytelling
- Difference between reporting data and telling a data story
- Combining data, narrative, and visuals
- Understanding the audience and decision context
- Identifying the central message
- Separating important insights from supporting details
- Building credibility through evidence
- Balancing accuracy, clarity, and persuasion
Module 10: Structuring an HR Data Story
- Establishing the HR or business context
- Presenting the key question or workforce problem
- Showing relevant evidence and findings
- Explaining the meaning and implications
- Developing actionable recommendations
- Structuring the story using:
- Situation
- Insight
- Impact
- Recommendation
- Creating an executive summary
- Developing an effective call to action
Module 11: Presenting HR Insights to Stakeholders
- Adapting the message for executives, managers, and employees
- Communicating technical findings in plain language
- Connecting HR findings to business outcomes
- Presenting sensitive or unfavorable results objectively
- Using annotations and emphasis to guide attention
- Responding to questions and challenges
- Communicating limitations and assumptions
- Building confidence when presenting data
Module 12: Ethics, Privacy, and Responsible People Analytics
- Employee privacy and confidentiality
- Responsible handling of personal and sensitive information
- Data minimization and appropriate access
- Recognizing bias in data and analysis
- Ethical use of employee information
- Avoiding discriminatory interpretations
- Transparency and accountability in HR analytics
Capstone Workshop: HR Data Story Presentation
- Analyze a sample HR dataset.
- Identify a significant workforce issue or opportunity.
- Select relevant metrics and supporting evidence.
- Create appropriate data visualizations.
- Develop an HR data story.
- Present insights and recommendations to the group.
- Receive feedback based on clarity, accuracy, relevance, and actionability.
