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Data-Driven Talent Acquisition: The Only Winning Formula

Article by Benjamin Sombi

Recruitment is one of the key pillars that support the success of organizations. With the emergence of online recruitment platforms and advancement in technology, there is a shift in how companies now acquire talent. Organizations need to hire the right people for the right jobs, who fit into the company culture. Achieving these goals using the human manual process is time-consuming and prone to people making errors. This is why leading organizations are taking advantage of data-driven solutions such as machine learning. They no longer follow the old recruitment ways. Machine learning is the process by which computers learn from vast amounts of data without being explicitly programmed.

 

A number of companies that lead in their industries are using data to not only find the right person for a current job but are matching long term and short term objectives to acquire the talent they need in the future. How we map people’s skills to roles have both short term and long term repercussions.

 

Companies can apply data-driven activities from the recruitment preparation stage. Often times, firms have a database of CVs from candidates that applied for jobs in the past. These CVs may still be relevant and some candidates can fit in the current company openings. Companies can use machine learning to pull out qualified candidates from the databases and then match with the current vacant. After matching the system can contact the top candidate and later on follow up.

 

Through social media, online professional profile building and recruitment platforms, companies can use machine learning to crawl the web to understand unstructured data. The likelihood of these models to find the best profile is high in a short period of time. The models will also be able to predict the probability of candidates looking for a job change.

 

Machine learning models can also help HR Managers to screen the best candidates from a pool of a number of candidates. The models can select high potential candidates and search for behavioral traits that will guarantee that the candidate will fit into the organizational culture. For example, Intuit recruits thousands of employees each year. They developed a system that is powered by machine learning to help them match and score potential candidates to open positions and based on competencies of top performers.

 

During the recruitment process, organizations will be searching for certain skills, personalities, online presence, religion belonging, etc. This is a tiresome job if it is done manually by a human being. It takes time and through fatigue, the HR Manager may end up making mistakes. Machine learning models helps in selecting the different characteristics the company is looking for in a short period of time. The candidates can then be prioritized based the important traits in each job

 

One of the world’s largest financial newspapers, Nikkei in 2018 mentioned that a firm in Japan called Recruit Holdings uses employee data, including personality assessments, working hours and performance evaluation, etc to identify people who are very likely to quit their jobs within six months. Managers will then sit down with the employees to hear out complaints and concerns. Another firm again called Recruit Sumai uses personality traits to identify dnew hires.

 

Recently machine learning models that analyses videos have been vastly improved. They are applied to detect a number of things by just analyzing the facial expressions and draw conclusions. HR Managers can make use of video analysis to pick out different personalities and attitudes of the candidate and check if it can match their culture. Vodafone uses machine learning-powered video interviews to assess candidates. They assess candidate suitability across more than 10 000 dimensions from body language and facial cues to voice pitch and speech cadence. Top candidates will then be invited to a face to face interview.

 

There is vast potential in terms of what data-driven models and artificial intelligence can do in the recruitment process. With the increasing power of computers, accumulation of data and theoretical understanding, data-driven initiatives in recruitment processes are advancing at a faster pace. The late Professor Hawking said in 2018, “Our future is a race between the growing power of our technology and the wisdom with which we use it. Let’s make sure that wisdom wins.” Therefore companies need to grasp the implications of this change. We look forward to what the future holds for us.

 

Benjamin Sombi is a Data Scientist, Entrepreneur, & Business Analytics Manager at Industrial Psychology Consultants (Pvt) Ltd a management and human resources consulting firm.



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