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Using and analysing HR data to drive performance
Your HR data should inform decisions about teams, not just populate spreadsheets. Choose relevant indicators, structure the analysis and make results understandable. Strengthen your ability to connect findings with HR priorities and managers' needs.
- Duration
- 3 days 21 hours
- Code
- RH024FR Code
Presentation
When data drives decisions, relying solely on intuition can undermine HR credibility. This intensive 3-day course teaches you to turn files from your HR information system into strategic indicators without writing a line of code.
The programme covers rapid data collection and cleaning, data structuring, visualisation in Excel/Power BI and interpretation of results. Every workshop draws on real cases, such as turnover, absenteeism and recruitment costs, that you can apply the next day.
You will leave with a ready-to-use method, dashboard templates and a presentation ready to send to senior management. HR becomes a business partner demonstrating the impact of its actions, backed by figures.
Objectives
By the end of this HR Analytics course, you will be able to:
- Understand HR analytics fundamentals: data types, KPIs, analysis levels and reliability best practices;
- select relevant indicators and build a consistent metrics framework across the HR lifecycle;
- apply analytical methods to key processes: talent acquisition, training, engagement and remuneration;
- design and interpret interactive dashboards to inform decisions;
- model HR business cases and quantify the ROI of actions such as training or turnover reduction;
- tell a story with data and translate findings into actionable recommendations;
- accelerate HR decision-making through evidence and facts;
- reduce costs and improve process efficiency in acquisition, absenteeism and productivity;
- increase HR credibility with the executive committee through robust, visual analyses;
- develop a data-driven HR management culture to drive performance and anticipate risks such as attrition, pay equity and workload.
Program
Module 1: Mastering HR analytics fundamentals and the data framework
- Introduction to the scope of HR analytics, its place in the organisation and its different approaches (HR, People and Workforce).
- Defining data types, quality and integration principles, and distinguishing KPIs from metrics.
- Building a data dictionary to ensure reliable exchanges and consistent HR analyses.
- Using tools and terminology: descriptive analyses, measures of central tendency and dispersion, and z-score calculations.
Practical exercises
- Clean an HR dataset and check its integrity before producing initial Excel visualisations.
Module 2: Modelling analytical journeys and the personnel selection process
- Understanding the three HR analysis approaches (descriptive, diagnostic and predictive) and the five stages of the analytical journey.
- Modelling the recruitment process (Talent Acquisition) using the 3F method and conversion funnels.
- Analysing costs and rates: acquisition, acceptance and candidate attrition.
- Using data to identify opportunities to improve recruitment performance and reduce costs.
Practical exercises
- Build a mini recruitment dashboard with key cost, time and recruitment effectiveness indicators.
Module 3: Assessing training ROI and developing L&D analytics
- Assessing training effectiveness through levels L1 to L4 of the Kirkpatrick model.
- Calculating training costs and return on investment (ROI) using scenarios and sensitivity analysis.
- Interpreting results and translating them into measurable management decisions.
Practical exercises
- Build a training ROI calculation model using Excel functions and numerical simulations.
- Complete a concise ROI case study and deliver a short, recommendation-focused pitch.
Module 4: Diagnosing engagement, absenteeism and productivity
- Analysing engagement and employee relations indicators: eNPS, absenteeism rates, attrition costs and early warning signs.
- Implementing workload analytics to measure time, workload and Full-Time Equivalent (FTE) balance.
- Interpreting capacity–workload gaps and detecting operational saturation points.
Practical exercises
- Assess engagement and absenteeism using real data and formulate operational recommendations.
Module 5: Analysing remuneration, benefits and pay equity
- Analysing salary structures, bonuses and benefits to identify gaps and management levers.
- Measuring internal and external pay equity using reliable indicators and simulation tools.
- Preparing and communicating results to senior management to inform budget trade-offs.
Practical exercises
- Simulate compensation and benefits optimisation and prepare key messages for management.
Module 6: Building an HR dashboard and communicating analysis through data storytelling
- Applying storytelling principles to HR data: from findings to decision-oriented recommendations.
- Guided introduction to Tableau and Power BI: data connections, hierarchies, filters, maps and charts (bar, line, waterfall, funnel and pie).
- Designing an executive HR dashboard summarising earlier analyses.
Practical exercises (final capstone)
- Build and present a complete HR dashboard covering TA, L&D, Engagement and Comp&Ben in a simulated 10-minute oral presentation.
Audience
This course is intended for HR professionals and managers seeking to manage their activities through data, including:
- HR managers monitoring key performance indicators to strengthen strategic decision-making.
- HR Business Partners helping managers interpret HR data to optimise action plans.
- HR controllers using HR reporting to assess costs, productivity and people-related risks.
- HR information systems managers structuring data collection and use for continuous improvement.
- HR consultants or project managers developing visualisation tools to improve operational management reliability.
Prerequisites
This course requires the following prerequisites:
- Professional experience: initial experience in HR, project management or indicator monitoring is recommended. It helps connect data analysis concepts to HR performance challenges.
- Basic knowledge:
- Proficiency in office tools such as Excel or PowerPoint;
- basic knowledge of database management and HR indicators;
- understanding of HR processes (recruitment, training and performance);
- curiosity about digital and analytical tools.
Teaching and assessment methods
- Initial skills assessment
- Training materials provided to participants
- Continuous assessment throughout the course
- End-of-course feedback questionnaire
- Combination of theory and practical application
- Attendance records
- Post-course follow-up evaluation
- Practical exercises
- Case study
Course highlights
- Expert HR data trainers: our trainers combine analytical expertise and hands-on HR management experience for concrete, credible examples.
- Practical, concrete approach: immediately apply each concept to your own data through Excel, Power BI and Tableau workshops.
- Accessible, current tools: use the same toolkit as finance departments, in real time and without coding.
- Strategic focus: link visualisations to business performance to demonstrate HR's impact on decisions and results.
Dates and sessions
Choose the date and delivery format that suit you.
No upcoming sessions are currently available.
Brand and software names mentioned in this course description, such as Excel, Power BI and Google Data Studio, are the property of their respective owners. Their mention for educational purposes does not constitute a commitment or partnership.