Technology Other News 27 Feb 2019 How AI and ML are re ...

How AI and ML are reinventing the talent assessment and acquisition space in India

Published Feb 27, 2019, 12:23 pm IST
Updated Feb 27, 2019, 12:23 pm IST
These tools enable recruiters to focus on responsibilities that add real value.
, AI and ML have made the hiring process more efficient by freeing recruiters and HR managers from the burden of performing repetitive tasks. (Photo: Pixabay)
 , AI and ML have made the hiring process more efficient by freeing recruiters and HR managers from the burden of performing repetitive tasks. (Photo: Pixabay)

Today, with technology having transformed the enterprise landscape, organisations across the globe are increasingly seeking to modernise one of the fundamental elements of any business – hiring. The proliferation of the internet and information technology about two decades ago spurred some ground-breaking innovations in the recruitment and hiring space. Since then, IT and digital technologies have matured significantly, paving the way for the creation of cutting-edge online recruitment tools and solutions.

The integration of tools like artificial intelligence (AI) and machine learning (ML) as a strategic deployment in modern talent assessment tools opens up possibilities for organisations to become more efficient. The relevance of modern assessment tools in the present job landscape is especially high, given how organisations must go through hundreds of thousands of applications at a given time to find the right candidates.


Process Efficiency

For one, AI and ML have made the hiring process more efficient by freeing recruiters and HR managers from the burden of performing repetitive tasks. Instead, these tools enable them to focus on responsibilities that add real value, and ensure that they are able to acquire the best quality of talent. Recruitment tools like talent assessment solutions take a data-driven approach to hiring, allowing organisations to automate the process and minimise human intervention within it. At the same time, the best AI-enabled solutions promise not only improved efficiencies but also higher candidate engagement to positively impact the quality of hires and their chances of retention.

Faster Initial Selection Process

Data-driven recruitment can help eliminate candidates who aren’t compatible, early in the recruitment process. Integrating automated shortlisting and real-time reporting to measure skills and performance benchmarks among candidates makes the talent pool smaller early in the recruitment process, thus, significantly reducing the time-to-hire. Once recruiters find the right benchmarks, they can automatically eliminate the candidates below a certain threshold and focus on those matching the relevant metrics. Besides information such as a candidate’s qualifications, skills, and experience, other aspects of their profile such as their interests, their values, etc. can also be leveraged to assess candidates. These data points on which candidates are assessed can be plugged into algorithms, and then, using machine learning, the assessment solution can predict how well they fit in with the organisational culture.

Predicts Future

During the shortlisting process, predictive analytics can also help forecast a candidate’s future performance to identify the top prospects out of several applicants. Recruiters can then create targeted interviews to map the strengths and weaknesses of each candidate and match them with the skills and abilities that a particular job role demands.

Why create a data-driven hiring strategy?

The adoption of technology as an enabler within organisations must be accompanied by a strong technology strategy to make its deployment truly successful. Data and analytics are making the hiring process more scientific instead of a trial-and-error based one, while AI and ML have made software smarter and capable of processing huge amount of data much faster. Adopting a data-driven hiring process also reduces the cost of hiring considerably; studies show that the cost of hiring can often be as high as 30% of the employee’s potential earnings in the first year.

HR teams can leverage analytics and machine learning to develop talent acquisition strategies and apply the same for subsequent hiring campaigns. A candidate management system can collect a large amount of data, and analysing these data sets can help recruiters identify specific trends such as:

Finding the primary sources from where candidates have been added to the talent hiring pool. Between referrals, professional networking sites, job boards or any other source, recruiters can focus their hiring strategy on those that are most effective for seeking out candidates.

Analysis of the data from these sources can help recruiters ascertain key geographies where candidates originate from to focus their recruitment campaigns on these areas.

Learn what are the top job roles that candidates in the system belong to, their key traits, etc. to understand them and target similar candidates for future campaigns.

Most organisations across the globe continue to face an acute shortage of talent. Hence, it becomes even more important for companies to target their hiring strategies to find employees with specific skill sets that match job roles and requirements. This can ensure sustainable growth for organisations in the long run, help them achieve higher rates of employee retention and stay ahead of the competition. A data-driven hiring strategy and automated recruitment process is, therefore, the most effective solution out there to achieve this efficiently.

--Mr Siddhartha Gupta, Chief Revenue Officer, Mercer | Mettl

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