Human Resources Analytics: Data Analytics In HR

Data analytics is in fashion. Undoubtedly, many of the most relevant innovations of recent years are linked to the emergence of Big Data and Data Analytics.

And in this context, using available data on workers and their activities to boost organizations’ business is becoming a fundamental element for adaptation and organizational development. This fact is undoubtedly motivated by data analytics’s success in consumer behavior, health, and energy consumption.

However, even if the reader is used to hearing about Big Data and has a more or less reasonable knowledge of the contents associated with said technologies, they are less likely to recognize what Human Resources Analytics (HRA) is all about. This article briefly presents the HRA’s main characteristics.

Although we opted for HRA in this text, the terms People Analytics or Workforce Analytics usually refer to the same elements.

What is Human Resources Analytics – HRA?

Data, indicators, and advanced statistical tools are the terms most commonly associated with ​​analytics. But HRA is more than that and contemplates other fundamental aspects such as identifying clear analysis objectives, good experimental designs that link the analysis with the organization’s effectiveness, or a clear work methodology that allows the different actors involved in the process to be involved. They are needed.

More formally, Human Resources Analytics is a methodology and an integrated process to provide evidence through data analysis that is used to improve the quality of decisions about people to improve individual and/or organizational performance.

It is, therefore, a matter of addressing the decision-making process regarding the workforce based on the evidence and knowledge obtained through data analysis. In addition, an important characteristic associated with this idea of ​​HRA is that these decisions about the workforce seek to connect the behavior of the members of the organization with its effectiveness understood in a broad sense (effectiveness as the satisfaction of the needs of the different interest groups that are influenced by the actions of the organization).

In any case, it is necessary to recognize that workforce analytics is not something new and that we have come across it out of the blue: as an example, Taylor’s “The Principles of Scientific Management” dates from the 1920s and the most recognizable “How to Measure Human Resources Management” by Jac Fitz-enz is published in the 1980s, both of the last centuries. Approximately 100 and 30 years ago, respectively.

Why this effort now with the HRA? Probably due to the combination of different elements:

• The clear verification is that the results generated by organizations increasingly depend on their workforce. In our knowledge economy, the individual is the main factor of sustainable advantage of organizations.
• Data’s extraordinary development (its generation, storage, and availability) on all phenomena (individual behavior included) and their analytics have had in the last decade. What has valued the great need for metrics to express the different organizational realities (that of the value of workers, too)?
• The promise associated with the HRA is to convert HR departments into true strategic partners for the organization.

What is HRA used for?

As we said before, HRA is a methodology that can be used for any decision-making process regarding the connection between the workforce’s behavior and the organization’s effectiveness.

Despite this, these years of implementation of HRA projects have revealed their usefulness in analyzing problems related to turnover, absenteeism, engagement, customer satisfaction, improvement of recruitment and selection processes, and predicting employee performance.

From the point of view not of the content but of the scope of the HRA, it is used to describe, explain and predict. These three scopes have different complexity and also different added values. Most organizations perform basic descriptive analysis, which is the basis of HR Reporting.

However, this descriptive analysis needs to provide more (or no) information regarding the causes of the relevant events and is not a helpful tool to act and modify reality. This requires more advanced analytics that allows us to predict and explain what interests us.

Explaining the phenomena offers us knowledge about their causes and, therefore, allows us to take action to modify what is necessary. Likewise, prediction allows us to advance decision-making by forecasting what will happen in reality.

What is an HRA methodology like?

Basically, an HRA project moves through a sequence like the following:

• The determination of relevant questions for the business (for the effectiveness of the organization).
• Identifying and using appropriate data to answer the questions.
• The application of both experimental designs and the appropriate mathematical and statistical techniques to obtain scientifically supported conclusions.
• Development of modes of communication in which the results are transferred to a language that is significant for the different groups receiving the analysis.

For this, different methodological and consulting models are used in which, firstly, work is done with the different interest groups of the organization to determine which are the aspects that strategically “concern” it.

Afterward, they work with the systems and human resources departments to access the data needed to be studied. After that comes the analysis work:

• preparing the data for analysis
• analysis development and
• study of the results obtained.

Finally, it is time to convert the results into value for the organization and, once again, exploit the results obtained with the different interest groups.

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