Working with HR Analytics involves more than just technology, data and analysis methods. It is a comprehensive process in which organizations deal with various aspects such as the company culture, employees’ knowledge and social-organizational processes. The key is to find a good balance between these elements. This is according to the research of John Werkhoven, who will receive his doctorate today from Nyenrode Business University. He examined the use of business analytics (data) in HRM and developed a model that shows what is needed to successfully work with HR data as well as how it can be used and further developed.
HR Analytics can be very beneficial to organizations. For example, a large firm with a high staff turnover rate used an analysis technique from consumer marketing to determine which mix of employment terms and working conditions would motivate employees to stay with the organization the most. Special teams then helped to formulate the optimal mix for each location, including elements like flexible work schedules, training opportunities and performance appreciation initiatives. After four years, the company was able to reduce turnover by more than 30% and achieve significant savings on its expenditures for recruitment, selection and training of new employees.
Over the last few decades, the use of Business Analytics in HRM (known as HR Analytics) has increased substantially. Still, many organizations struggle to obtain good data and analyze it in a way that yields insights for targeted, concrete decisions and actions.
How does Business Analytics work, and why is it so difficult? To answer this question, Werkhoven developed a model that shows how Business Analytics works and what is needed to use it successfully. The model consists of several steps, leading from data analysis to insights, then from insights to decisions. To perform HR Analytics, an organization must use its business analytics capabilities: in other words, the ability to do things with HR Analytics using the organization’s available resources.
These business analytics capabilities can be divided into five main groups: Technology, Governance, People, Culture and Analytical Practices. These capabilities do not exist in isolation, but instead influence one another. They can strengthen one another, but they can also get in the way. An example is an information system that has numerous features, but people can’t work with it because they haven’t been properly trained or because the system isn’t user-friendly. The key is to coordinate all these capabilities and ensure that they function well together.
In addition to identifying these capabilities, Werkhoven also looked at how they are used for HR Analytics. In doing so, he examined four mechanisms for the use of HR Analytics. The first of these is exploring the possibilities with data for a specific purpose in a specific context. The second mechanism is “sense-making”: obtaining insights from data. This is a process with several (conscious and unconscious) steps which often involve the use of certain “frames”, or ways of structuring the data for ourselves. The third and fourth mechanisms are exploiting the benefits of information and harnessing synergy between capabilities, respectively.
Werkhoven’s research reveals that many components and mechanisms influence the successful use of HR Analytics in organizations. This in turn makes it a difficult, continuous process for organizations to strike the right balance between capabilities and processes. Other factors play a role as well, such as “data versus intuition” when making decisions and the ethical aspects of data use. With the further development of technology and the possibilities of data (including Big Data), these considerations are becoming increasingly important. That doesn’t make things any easier for organizations. Werkhoven’s research can help to understand these complexities.
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