Recently, the Kara RH team has had the opportunity to participate in several events dedicated to HR professionals. One thing is clear: everyone seems to be using People Analytics. However, when we dig deeper into the subject, we find that a large proportion of these people only use statistics. That's why we felt it was essential to write an article that would make the distinction.
People Analytics and statistics are two concepts that may seem similar at first glance, but which play distinct roles in human resources management. While both use data to inform decisions, People Analytics goes far beyond the simple interpretation of numbers. This article explores the fundamental differences between these two approaches, highlighting their respective uses in an HR context.
Definitions and objectives: what are HR analytics and statistics?
Statistics
Statistics is a branch of mathematics that focuses on the collection, analysis and interpretation of data. In human resources, they are often used to provide descriptive performance indicators, such as employee turnover rate, absenteeism rate or average salary. The aim of statistics is to summarize data in order to derive trends or observations about the current state of an organization.
People Analytics
People Analytics, on the other hand, is a discipline that uses HR data to generate strategic insights for informed decision-making. It uses statistical methods. This means that statistics is a subset of People Analytics. It's not just about describing what happened but anticipating what's going to happen and making recommendations. People Analytics relies on more advanced tools, such as predictive models and artificial intelligence algorithms, to help companies optimize their talent management.
Descriptive versus predictive approach
Descriptive statistics
In HR, descriptive statistics are often used to measure past or present phenomena. For example, we calculate the voluntary turnover rate over a certain period to better understand team stability. However, they do not allow us to anticipate causes or predict future departures.
Predictive Analytics
Unlike statistics, People Analytics is forward-looking. Using predictive modelling techniques, such as regression or machine learning, HR professionals can anticipate future employee behaviours, such as the risk of departures or absenteeism. Predictive Analytics goes beyond simply describing current or past situations; it can answer complex questions such as “Which employees are likely to leave the company in the next year?” or “Who is at risk of going on disability?”.
Exploring cause and effect: a more in-depth approach
Statistical analysis
HR statistics often focus on univariate (one variable at a time) or bivariate (relationship between two variables) analyses, such as the link between seniority and employee performance. This enables simple relationships to be understood, but interpretation remains limited.
People Analytics and root cause analysis
People Analytics goes a step further by exploring several variables simultaneously to identify the underlying factors influencing employee behaviour. For example, rather than simply looking at turnover rates, People Analytics can help identify whether poor management, inadequate compensation or unfavourable working conditions are the real causes of departures.
Real-time data use and decision-making
Traditional statistics
Statistics provide a snapshot of a situation at a given point in time. They are often based on historical data and, while very useful for reporting purposes, they are not always relevant for rapid decision-making in a constantly changing HR environment.
Real-time People Analytics
With People Analytics tools, managers can access data in real-time. This enables ongoing HR strategies to be adjusted, anomalies or opportunities to be detected quickly, and more agile decisions to be taken. For example, by continuously analyzing employee feedback, HR teams can intervene earlier to improve engagement or anticipate training needs.
Complexity and tools used
Statistical tools
Statistical tools commonly used in HR include Excel, statistical software or HR management systems that provide reports on key indicators. These tools are suitable for reporting tasks and descriptive analysis.
People Analytics tools
People Analytics involves more sophisticated technologies, such as artificial intelligence platforms, advanced analysis systems (like Kara or Power BI) and machine learning algorithms. These tools can identify complex patterns in data and automate certain tasks, such as detecting the best candidates or proactively managing talent risks.
Business context and strategy: beyond the numbers
HR Statistics and reporting
Statistics provide reliable information for reporting and answering standard questions, such as “How many people did we recruit this year? Or” What percentage of women are in management positions? While such information is interesting, it remains limited in terms of strategic analysis.
People Analytics as a strategic lever
People Analytics is a strategic tool. It enables organizations to align talent management with strategic business objectives. For example, by determining the skills that will be needed to achieve objectives, HR professionals can better plan training programs or recruitment strategies, ensuring that the organization has the talent it needs to grow and innovate.
In short, statistics play an important role in monitoring and reporting HR data, while People Analytics go far beyond, offering broader perspectives and enabling strategic decision-making. Indeed, you can start your initiative with statistics, and as you mature, you can apply People Analytics. This will enable companies to better understand their human capital and anticipate change while optimizing their talent management for the future.
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