Artificial intelligence and the employee lifecycle

Hiring the right people for the job is one of the most important missions for the Human Resources department.

Be it due to fast expansion or turnover, unexpected job openings can rush HR and managers, which are more likely to hire the wrong person due to time constraints. This is one of the reasons why companies are turning to artificial intelligence to optimize their processes.

When people make decisions under pressure, they usually choose the quickest and easiest option possible, which isn’t always the best. It’s not because they want to make a bad decision, but to fulfill a need as timely as possible, going by instinct instead of data is the common route. Unfortunately, rushed hiring decisions have a higher risk of resulting in disappointment for all of those involved.

Another challenge HR faces is people management, which is often done in a reactive way – basically trying to put out fires as they pop up. However, AI can help in this camp as well, predicting needs from onboarding all the way to turnover.

In this article, you will see how the combination of the knowledge possessed by team leaders and the power of technology allows for data based insights that improve the quality of decisions all across the board. 

 

Hiring

For recruiters that receive a large amount of CVs at once, it’s hard to have a measurable impact on the quality of hiring when using traditional screening processes. Going through the information of the candidates takes a considerable amount of time and effort, and usually means that recruiters have little to no time to think about the company’s strategy and suggest improvements in the hiring process as a whole. To put it bluntly, they are simply overwhelmed.

Furthermore, it is humanly impossible to analyse all of the applicants, and this can result in not only injustice (since some candidates won’t even have a chance) but also an inefficiency, as the best candidate for a particular job opening could be lost in the process.

This is where the power of Artificial Intelligence can be extremely useful: due to its immense data processing capabilities, AI can go through thousands of CVs in a matter of seconds, guaranteeing that each candidate has a fair chance. Additionally, as no sensitive data is used within the process, when used correctly AI algorithms can reduce subjective decisions which could be biased.

By making the hiring process faster and more assertive, AI can support recruiters’ decisions and free up some of their time, so that they can focus on tasks that require more strategic thinking.

 

Performance and Training

The use of data analysis helps employers discover what exactly makes a employee excel at their job, and in turn, this data can also be used to identify the best candidates for job openings, based on specific criteria such as ability to persuade, or the ease to form harmonious relationships with peers. But the use of AI goes beyond hiring.

Artificial intelligence can use both historical data and machine learning to predict the most probable future outcomes. RH can then identify issues regarding performance ahead of time, and act accordingly to remediate them, by building a training program or finding news ways to boost employees’ motivation. By optimizing analysis and planning, AI helps People Management become personalized, being tailored to each department’s needs.

Thus, Artificial Intelligence can be used to make companies more people-centric, by helping HR to motivate employees, reducing bias within performance evaluations and building more assertive training programs.

 

Turnover

Human capital is one of the factors that have most influence in a company’s bottom line. Turnover, for example, is very costly when you take into account the hiring process, the onboarding, and the drop in productivity that happens until the new employee gets up to speed. 

Here, artificial intelligence can help in two ways: first, by optimizing the hiring process, recruiters can fill roles faster and reduce the productivity loss caused by turnover. It’s not just a matter of speed, but also quality – by recruiting the right candidate, you ensure that the work will be done in the best way possible.

The other way AI can help with this issue is by predicting turnover. By observing patterns in employees who have already left the company (such as absenteeism), the system can interpret current employees’ actions and alert HR when it identifies people who are falling into these behaviour patterns. With this foresight, HR can prepare, either working to prevent turnover or simply by starting the search for new candidates.

 

Promotion

Artificial intelligence can also be used to analyse data on employee performance, providing managers with quick access to performance metrics regarding their teams. These metrics can also include behavioral evaluations.

This application of AI can help managers have a clearer view of which employees are excelling at their jobs, and ensures that any decisions regarding promotions are made based on transparent criteria, without the interference of unconscious bias. Thus, other team members are able to know exactly what they are expected to do and improve in order to receive a promotion or salary increase.

 

Case Study

For each business’ needs, it is necessary to develop a specific algorithm and train mathematical models to learn from the past data so that they can accurately predict future outcomes. For this reason, Rocketmat, an AI company specialized in handling HR data, creates algorithms that are tailor made according to what each project demands.

Selected in 2018 from a pool of several other tech startups by one of the world’s largest breweries, Rocketmat was enlisted to help identify behaviour and competencies needed to work in highly automated and technological industrial environments. To this end, our team modeled two types of algorithms capable of understanding different levels of hard and soft skills in teams, departments and all of the breweries’ units.

Rockemat analysed data from approximately 40 thousand professionals (all anonymized), which made possible the development of an algorithm that can identify competency gaps. This gave HR the opportunity to plan the employees’ career development in order to bridge those gaps. It also gave them a better understanding of the performance evaluation process and improved people management strategies.

Another algorithm was implemented in the hiring process, to find a “match” between the candidates and the characteristics required by the company, making sure that the entire employee lifecycle was off to the best start possible.

With a more assertive hiring process, the time to fill roles was reduced, from 45 days down to 23 days. 200 candidates were selected using this technology, from people who were new to the job market, at 18 years old, to more seasoned professionals (an average of 47 years old). 75% of the candidates selected by AI matched the company’s needs. And beyond efficiency gains, the company also observed a gain in diversity using the new hiring process.

The use of AI allows companies to automate and standardize processes. Especially for those that hire on a large scale, standardization is important to ensure the company’s culture remains strong and clear to all employees. These tools might not be as wide spread yet, but in the coming years Artificial Intelligence is sure to become essential support to HR in organizations that want to succeed in the long term.

 

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