Analytics for predictive HR

Today’s analytical tools allow you to combine several sources of information for a more personalized form of management.

The earliest types of IT tools in the 1970s were designed for personnel management and payroll calculation. In France, the GPEC agreements (job and skill management) in 2005 were required before implementing a PSE (job protection plan) and this forced companies to be equipped and anticipate their needs in terms of HR management.  HR solution providers invested in new functions, such as learning, skills and recruitment, integrating them into their ERPs. The models used by HR departments were, however, difficult to implement and highly unpractical and not context-sensitive. Faced with pressing legal obligations, French companies realized they had not anticipated problems related to managing skills and were unable to determine their own needs.

A multitude of niche solutions specializing in training and talent management emerged in the 2005-2010 period. It was not only difficult to create models for databases of jobs and skills, but it was also a challenge to ensure consistency between all these tools: skill models, job databases, training catalogs, annual interview content, etc. In order to obtain an effective talent management, we needed to review the organization of HR and its processes.

The tension in the job market has accelerated the process, because we have had to organize and set up tools to attract and keep new talent. The challenges of the GPEC are now more evident than ever and talent management tools have improved to the point where they provide greater coverage, from sourcing to employee retention and training.

HR analytics has thus become crucial for HR departments to handle overall management and support their role as a provider of services to their internal customers – the managers and employees – and better retain them. For example, HR analytics  can be used to measure and analyze absenteeism and turnover within a business unit to set up the appropriate measures, especially in terms of management.

HR’s heightened awareness of HR Information Systems

HR must continuously optimize its processes because practices change very quickly. The new generations of employees working in HR are more familiar with new work methods and have been trained in the use of more agile IT tools. All these high-performance tools provide very accurate indicators that HR personnel can use to defend their policies with their top management. Today, such tools are capable of very accurately analyzing occupational risks, deal with legal obligations (hardship, senior employees, equal opportunity) or show the positive effects of a training campaign.

Predictive analytics in HR to better anticipate situations

HR analytics has become more efficient in interpreting data, enabling HR to become predictive, essentially through the use of simulations. Pressing and urgent demands have been made by top management in terms of planning ahead, particularly to ensure their digital transformation and increase responsiveness in unpredictable business situations. HR departments also need to be able to get a better understanding of people’s profiles and their ‘soft skills’, which are based on emotional intelligence and take into account more subtle skills that  rely on common sense and social intelligence. Recruiters should try find the balance between hard skills and soft skills in an employee’s profile to be able to meet their needs.

Defining a proper model for managing talent, in particular a database of skills, is a key challenge. Such a database should be based on a company’s needs: transfer, career development, acquiring new skills. Analytics requires an IT system capable of cross-referencing all the data. HR professionals must be efficient and capable of recognizing the appropriate data required to do their job.