The ADNe is the psychogenic algorithm developed by researchers Elías Azulay and Vicente Bufort, that governs the world of emotions. The algorithm consists of a universal numerical pattern that deciphers our behaviour.
Each individual has a unique emotional model, this is based on the biological performance level of the genes that produce the enzymes responsible for the biosynthesis of each molecule that belongs to the metabolic pathway, where the main neurotransmitters that govern our behaviour sit. Something like a “fingerprint” are almost invariable. There are nearly 370 million emotional intensities and our personality is the reflection of more than 19 million oscillating combinations that we could call our “personal brand”.
Elenius The Recruiter, the only Spanish robot that makes personnel selections, has carried out a study on more than 2,100 candidates who applied for a job proposed by a well-known textile multinational. Elías Azulay tells that; “42% of the candidates pay complete attention for more than three minutes. However, the remaining 58% showed that once they have exceeded this time, they stop trying to apply for the vacancy.” Likewise, the study shows that 33% had a minimum experience of 6 months in the position, and that only 3% have the specialisation requested.
Elenius has made a filter where you can view the candidates in terms of emotional characteristics required to successfully undertake the proposed functions in the role, the number of suitable candidates is set at 36%. This number is reduced to 24% as soon as the coincidence between the city of residence and the work location is determined; so we understand that geographic mobility is a very powerful factor that should not be given more attention.
Although candidates are not required to state their age, this filter is used and often demanded by the companies hiring, this amount is reduced to 20% as soon as it is applied. If we take into account the academic studies, only 20% of total candidates would pass to the next screen, while if we measure a minimum experience of six months in a similar position, the result will be that we can consider 11% of the initial sample.
In this case the company was requesting specific experience, which meant the remaining candidates was reduced further to 1.8%, while if we try to square the hourly conditions, this indicator is reduced to 1.6%.
The conclusions of this study, help us to understand the impact of Big Data in the distribution of information and the lack of precision, both in the employers and in the candidates.
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