HR Analytics
Organizations can use HR Analytics as a tool to optimize both their business performance and the employee experience based on facts. HR Analytics differentiates itself because it uses data to gain insights and make recommendations. For every modern organization with an awareness of the enormous difference employees can make in the implementation of organizational strategies, and of the importance of keeping staff costs under control, HR Analytics is an essential discipline. AnalitiQs helps organizations implement HR Analytics and develop skills in the field of HR Analytics.
Why HR Analytics?
- Organizations that base their decisions on data-driven insights perform better. The use of data in the decision-making about an organization’s human capital, the organizational structure and the performance of the HR function is also referred to as Human Resource (HR) Analytics, or data-driven HR.
- The success of organizations is often determined by the people who work there. And as the direct and indirect costs associated with hiring these people account for a significant part of a company’s total costs, HR Analytics can be of great importance to all organizations.
- Since the beginning of the 21st century, the field has undergone enormous development.
Definition of HR Analytics?
The words ‘HR Analytics’ indicate that the field is about (statistical) analyses. That doesn’t cover it all, though. The bigger goal is to provide relevant insights into human resource and organizational topics. The process involves different tools, depending on the problem and the context. This could be a (statistical) analysis as well as an employee survey or an HR Dashboard. So, the goal isn’t really to build a predictive model, for example. The goal is to answer the question as accurately as possible using the correct data and the right tools, depending on the context.
Succes with HR Analytics
Many organizations already have the people to work with HR Analytics. Think for example of Business Intelligence Developers, Data Scientists and Research Analysts. And yet, most organizations fail to create tangible value from the HR Analytics efforts made by these experts.
It requires more than simply adapting some technical profiles for HR Analytics to be successful and for an organization to really make the transition to data-driven HR. If you want to be successful, you need to operate at multiple levels simultaneously.
For example:
- It’s important that the HR Analytics efforts (supply) are aligned with the demand from the line (supply).
- This requires selecting and activating the correct technology.
- You’ll need an HR Analytics target operating model, which includes at least a Translator role.
- Data needs to be generated and administered.
- The necessary Privacy and Security measures must be put in place.
- And last but not least, the HR professionals need to be trained, so they know how the insights can be used.
Where to start?
Successful use of HR Analytics doesn’t happen overnight. The adoption of HR Analytics is like a journey that starts with a destination and is subsequently divided into stages.
Baseline measurement
If an organization is serious about using HR Analytics, the best way to start is with a baseline measurement. Where is the organization now when it comes to aspects like data, operating model, technology, privacy and security management measures, leadership, skills, strategy/research questions? Perhaps there are already some successes to build on?
Goal & Stages
Once the starting point has been defined, it’s time to decide about a destination, divide the journey into stages and within each stage, work towards the finish line of each HR Analytics stage in an agile way.
Want to read more about HR Analytics?
Irma Doze, the founder of AnalitiQs, has a great passion for data. In collaboration with Toine Al she wrote the book “HR Analytics – Creating value with data-driven HR policy”.
This book provides a step-by-step guide to how HR Analytics can be applied to create value for an organization. This data-driven approach enables HR to increase the job satisfaction and performance of the employees and improve the performance of the organization even better.
HR Analytics examples - HR Data Analysis
HR Analytics examples - Employee Surveys
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