In an increasingly data-driven business world, Business Intelligence & Analytics also plays a central role for modern HR departments. The special methodology of people analytics offers valuable insights into the workforce, enables data-based decisions and contributes to the optimization of HR processes. In this article, we will highlight the most important aspects of people analytics and answer questions such as: What is People Analytics? How does people analytics work? What are the key stages of people analytics? And, of course, at the end of the article, we will look at examples of people analytics.
What is People Analytics?
People Analytics Definition: People Analytics, also known as HR Analytics or Talent Analytics, refers to the use of data analytics techniques to gain deeper insights into the work environment and employee behavior. This practice involves the collection, analysis and interpretation of HR data to identify patterns and support strategic decision-making. People analytics can be applied in various areas, including recruitment, employee development, performance management and employee retention.
Areas of application in companies (People Analytics examples):
- Recruitment: Optimization of the recruitment process through analysis of applicant data.
- Employee development: Identification of training and development needs.
- Performance management: evaluation and improvement of employee performance.
- Employee retention: Predicting dismissals and developing employee retention measures.
How does People Analytics work?
People Analytics is based on a structured process that consists of several steps and is ideally mapped out in a holistic HR Analytics Solution :
1. data collection: The first step in people analytics is the collection of relevant data. This data comes from various sources, such as
- Employee surveys: Regular surveys on employee satisfaction and commitment.
- Performance evaluations: Assessments of employee performance by superiors.
- HR systems: Data from payslips, attendance records and employee files.
- External sources: Market and industry data that can be used for comparison purposes.
2. data analysis: Once the data has been collected, it is analyzed using various methods and tools. These include:
- Statistical analyses: Identification of trends and patterns in the data.
- Data visualization: Creation of graphics and diagrams to present the results clearly.
- Machine learning: use of algorithms to predict future developments and behavior.
3. interpretation of the results: The interpretation of the analyzed data is crucial for deriving recommendations for action. HR experts use their specialist knowledge to evaluate the results in the context of the company's objectives. This makes it possible to develop and implement targeted measures based on the findings.
By combining advanced analytical techniques and human expertise, People Analytics can help companies make informed and strategically valuable decisions.
What are the key stages of people analytics?
People analytics can be divided into different levels, each offering different types of insights and analysis:
Descriptive analysis: This stage answers the question: "What happened?" It involves the basic analysis of historical data to understand past events and trends. Example: Analysis of employee turnover in the last year.
Diagnostic analysis: This stage goes one step further and attempts to explain why certain events have occurred. It examines the underlying causes and correlations. Example: Analyzing the reasons for high staff turnover in a particular department.
Predictive analysis: This is the prediction of future events based on historical data and patterns. Example: Predicting which employees are most likely to leave the company in the next six months.
Prescriptive analysis: The prescriptive analysis provides concrete recommendations for action based on the findings of the previous stages. Example: Development of an employee retention program for at-risk employee groups.
People Analytics examples
People analytics personnel development: An important application example is the identification of talent and development paths. By analyzing performance data and career paths, companies can identify promising employees and promote them in a targeted manner. This leads to better talent development and long-term employee retention(article on employee retention and engagement).
Optimization of the recruitment process: Another example is the optimization of the recruitment process. By analyzing applicant data, companies can improve the selection process, identify the best candidates more quickly and increase the recruitment rate. This saves time and costs and increases the quality of new hires.
Employee retention: People analytics can also be used to predict and reduce dismissals. By analyzing employee satisfaction, commitment and other factors, companies can identify employees at risk at an early stage and take targeted measures to improve working conditions and increase employee retention.
Is people analytics AI?
Artificial intelligence (AI) plays an important role in people analytics, especially when processing large amounts of data and performing complex analyses. AI-supported systems can recognize patterns, make predictions and provide recommendations that go beyond traditional statistical methods.
Difference between traditional analyses and AI-supported analyses:
- Traditional analyses: Based on statistical methods and often require manual data processing and interpretation.
- AI-powered analytics: Use machine learning and algorithms to automatically analyze data and gain deeper insights.
People analytics for the use of AI:
- Chatbots: Automated communication tools for answering HR-related questions.
- Predictive analytics: Predicting employee behavior and trends based on historical data and patterns.
Why People Analytics?
Strategic advantages: People analytics offers a variety of strategic benefits. By using data-based insights, companies can make informed decisions, increase employee satisfaction and retention and improve the efficiency of HR processes. This leads to better overall business performance and competitive advantage.
Economic advantages: People analytics also helps to reduce costs. By optimizing recruitment processes, improving employee retention and identifying inefficient HR practices, companies can achieve significant savings. In addition, data-driven HR development increases the company's productivity and innovative strength.
Future-proofing: The use of people analytics helps companies to better adapt to market changes and become future-proof. By continuously analyzing and adapting HR strategies, companies can react to changes in the workforce and to external challenges. This promotes an agile and resilient corporate culture.
Conclusion
People analytics is a powerful tool that enables companies to make informed and strategic HR decisions. By combining data analysis and human expertise, companies can optimize their HR processes and achieve long-term success. The use of artificial intelligence expands the possibilities of people analytics and offers deeper insights and more precise predictions. Companies that use people analytics are better equipped to meet the challenges of the modern labor market and manage their employees successfully.
