Artificial Intelligence and Machine Learning will have a serious impact Human Resources. Algorithms are starting to feed decision support tools into business processes: sourcing, recruitment, skills, mobility, loyalty, training, compensation, benefits, absenteeism, etc. Everything can be optimized.

Human capital, the main asset of the company, can now be made more valuable thanks to the analytical solutions currently available to companies based on Big Data and Artificial Intelligence (AI). The role of Human Resources (HR) in our digital environments is changing and must become more efficient and predictive. New decision support solutions impact the entire HR value chain, as well as the efficiency, performance and growth of a company. On top of this comes the considerable advances in neuroscience, which force us to consider the collective differently, particularly through new methods such as neuro-management.

Where does this apply to Human Resources?

For example, during recruitment phases, “chasing” high-level profiles or identifying high-demand skills can be extremely time-consuming when it comes to poaching people, or expensive when hiring head hunters.

Currently, looking only at France and its 29 million assets, half, 14 million in 2017, are registered on LinkedIn, versus 5.5 million on Viadeo*. In addition, 83% of job seekers say they use the internet. In 2016, according to APEC, 7% of managers changed their company. 9% changed positions internally. Among non-mobile executives, 72% took steps to give a new boost to their careers.

Machine Learning algorithms for HR:

To identify these professionals who are just keeping an eye out, actively searching, looking for a change or available on the market, with sought-after skills or significant achievements, using machine learning algorithms becomes a real boon, if not a necessity, for Human Resources in our hyper-digitized environments. The idea is to reduce acquisition costs and time, while limiting turnover. An AI Sourcing model allows the processing of data external to the company, which comes from employment platforms and social networks via talent acquisition software.

It is also necessary to treat the internal data. When recruiting, a company receives an average of 250 applications. How is it possible to identify the best elements? The acquisition software provides upstream filtering on the most relevant keywords and skills. This is done by crossing the data with the development of in-house expertise that has been most useful to the company. Evaluation data during a job interview can be added to the model.

These elements together help optimize recruitment roadmaps and improve their quality.

Employees, co-creators of culture and value:

Artificial Intelligence also allows the implementation of actions to promote loyalty, limiting an often very expensive turnover, a key HR issue. How? By identifying what keeps employees in the company and what causes them to leave their positions. For the majority of employees and especially for millennials, career changes and training are more important than salary (Yellow Recruiting 2016 study).

Given the diversity of situations to manage, the HR manager must be “aware” and flexible. They need to possess knowledge that is as up-to-date as possible on the development of internal skills versus the needs of the company and the evolution of the market. For this, companies rely on a finer analysis of corporate data. But before the analysis, it is still necessary to produce this data.

In the digital age, the employees themselves are the best ambassadors. If their company produces information, they will share it on social networks.

They are also co-creators of culture and value for their business. By setting up digital platforms for sharing knowledge and expertise within the Corporate Social Networks (CSN), the HR departments feed emulation and cohesion of the teams within the group. Recommendation engines make it possible to customize access to information from the platforms. These tools will generate data, revealing expertise, interests and talents. They will increase the engagement factors. Machine Learning technologies can support the employee in their evolution within the company by making recommendations and offering services.

Improved employees

The challenge for HR through these new technologies is to facilitate the identification of high potential profiles. Having a vision of the personnel’s professional interests makes it possible to respond to them through internal mobility and training proposals in order to stem turnover. It is then possible to manage the profiles or jobs at risk.

Added to this are neuroscience, the results of cognitive and personality tests associated with performance and productivity indicators. Today Artificial Intelligence allows the measurement of behavioral traits. Because apart from skills, behavior is responsible for nine bad castings out of ten.

Another commitment factor and quality feedback, and not to be underestimated, is well-being at work. The Chief Happiness Officer can talk about it. Algorithms can measure it. The role of the HR department of tomorrow will be as conductor of the emotional and relational intelligence directed towards a common goal and federator of the company.

Appearance of the Big Data HR Project Manager

In concrete terms, the company must anticipate the needs of future expertise and give the means to its employees and providers to compose the best project teams on a given subject at moment T, and almost automatically. In a group of several thousand employees, the fields and specialties are indeed very numerous.

Some large organizations have now recruited their HR Big Data Project Manager, such as Orange. With respect to the HR Open Source movement, it proposes to share Human Resources Data and recruitment. Dell and Oracle have joined. Another example, Adecco and the La Poste group retrieve and process the data of applications through chatbot exchanges. The Expedia travel site uses a semantic analytics solution that has enabled it to receive higher quality applications, increasing the number of job interviews by 33%.

Today, the value of human capital can be measured or even redefined in a world where the collective reinvents itself every day.

[Photo: Annie Spratt Unsplash]

Source:

APEC, Panorama des mobilités professionnelles des cadres, June 2017
Study Towers Watson
Study Yello Recruiting 2016
INSEE https://www.insee.fr/fr/statistiques/3535797

L’ADN http://www.ladn.eu/entreprises-innovantes/comment-lintelligence-artificielle-redefinit-les-rh/
Forbes https://www.forbes.com/sites/zackfriedman/2018/08/06/ibms-hr-chief-shares-best-advice-on-the-future-of-work/
RH Info https://www.rhinfo.com/thematiques/management/neurosciences-et-management-equitable
Le Mag IT https://www.lemagit.fr/conseil/HCM-SIRH-promesses-et-menaces-de-lAI-pour-les-RH
Couthon Conseil http://www.couthon.com/blog/le-big-data-en-ressources-humaines/
Lebigdata.fr https://www.lebigdata.fr/rh-et-big-data
Le Figaro http://www.lefigaro.fr/emploi/2017/01/17/09005-20170117ARTFIG00290-les-francais-cherchent-un-emploi-sur-internet-mais-le-trouvent-grace-a-leur-reseau.php
Le blog du modérateur https://www.blogdumoderateur.com/panorama-reseaux-sociaux-france-monde/

*Viadeo has not supplied new figures since 2013

octopeek icon

Retrouvez l'essentiel de l'actualité "Big Data" en vous inscrivant à la newletter Octopeek

 

 

Félicitation, vous allez recevoir le livre par email