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Matching prédictif

How do you predict success in a job today?

eye 25 Published on 21 Sep. 2022
How
tag #Predictive Model

Faced with complex challenges such as the hybridization of professions, the shortage of talent, the lack of skills, being able to anticipate the potential, skills and behavior of candidates is crucial for any company.

Today, companies need people who can learn new skills, be proactive, know how to quickly transfer these new skills to their missions and also adapt to the corporate culture.
 
It is therefore necessary to approach competence differently, by considering it in a broader and more versatile dimension.

Competencies as a success criteria

Revealed in recent years, transversal skills have naturally imposed themselves as the solution to recruitment difficulties, in addition to presenting themselves as the predictive element of success in a position today.

With transversal competencies, we are on the know-how and the practical knowledge that when well mastered, allow an individual to respond effectively to the requirements and challenges of everyday life.

The transversality of the skill takes on its full meaning in the person's ability to correctly mobilize and use a skill at the right time, and above all, to know how to reinvest it in different situations of their personal and professional life.
 
This skill has a universal composition and is thus valuable in different professions and valid for all sectors of activity. Little impacted by the too rapid evolution of technical skills, decompartmentalized jobs and training, generalizable to all, easy to interpret, transversal skills are also perfectible and tend to be sustainable over time.

Here are four characteristics that make it a quintessential skill:

  • it is dynamic, in the sense that it mobilizes different knowledge of the individual in its implementation;
  • it is evolutionary, since it is in permanent construction and is perfected throughout life;
  • it is empowering, because it places the individual at the heart of his own development to make him move towards a knowledge of becoming;
  • it can be assessed, because it can be measured and a margin of progress can be determined.

Maximise your hiring using predictive analytics

Anticipate skills with predictive analysis

Predictive analysis consists of analyzing, using complex algorithms, a large volume of data in order to anticipate the behavior of candidates and employees, reduce the risks of a bad hire, predict the evolution of skills, improve commitment and prevent departures.

If human decision-making involves an element of intuition, predictive data analysis is the opposite since it is essentially done in a logical way. It is a question of objectifying as much as possible the information produced in order to secure the decision as much as possible, on more-than-complete information, which would escape the human brain.

The objective of predictive analysis is not to replace HR actors, but to support them and help them in their decision-making. Predictive analysis is a work tool, at the service of HR. It performs finer, faster, more complex and less biased actions than humans. It processes and provides reliable and objective information that the HR professional uses to accomplish his missions more effectively.
 
The HR professional does not stop thinking. They must consider the data analyzed and make the necessary decisions. Only, their decisions will only be better. They also retain the relational dimension specific to his profession: “human” resources.
Predictive analysis, comparable to a machine, cannot take on this socio-emotional role; it cannot explain a decision tactfully, skilfully use influence in negotiations, accompany a human being with kindness, manage conflict in a competent manner, deploy communication adapted to the different people in the organization, etc.

It is therefore a marriage of convenience between artificial intelligence (AI) and human intelligence (HI). The AI ​​analyzes and the human observes and decides.

To learn more, download our ebook on predictive analytics!

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