Predictive Analysis in Employee Retention and Candidate Success


Predictive Analysis in Employee Retention and Candidate Success

Posted on 14 March 2024

Predictive Analysis in Employee Retention and Candidate Success

​​Artificial Intelligence in Human Resources

In 2019, former IBM CEO Ginni Rometty pointed out the shortcomings of traditional human resources (HR) methods for American workers and advocated for the integration of machine learning to enhance HR efficiency. IBM's fiscal year 2019 saw artificial intelligence (AI) savings soaring to a staggering $300 million.

Today, predictive AI has progressed significantly, enabling companies to predict employee departures and determine the necessary salary adjustments for employee retention. Strategies such as personalized employee experiences and unbiased performance evaluations are also becoming pivotal in fostering workplace inclusion.

Elevating Employee Retention with Predictive AI and KPIs

Enter Bob, a pioneering HR platform founded in 2015. Bob goes beyond the conventional by enhancing employee engagement through features like work anniversaries and performance shoutouts. This platform empowers users to measure crucial metrics—growth, retention, and absenteeism—while generating insightful HR reports based on key performance indicators (KPIs).

Addressing concerns about AI replacing the human touch in HR, an article on the Bob site discusses how AI insights, like those from Facebook, reveal that employees neglecting annual surveys are 2.6 times more likely to leave their roleswithin six months. Armed with knowledge about signs of employee dissatisfaction, companies can proactively plan for hiring needs, intervene with promotions, and address underlying issues contributing to discontent.

For some companies, retention remains a formidable HR challenge. Most Loved Workplace, a company certifying highly desirable employers, asserts that 27% of an employee's decision-making process to stay is influenced by compensation and benefits. Despite the usual budget constraints, mastering employee retention is key.

Unveiling Potential with Bias-Free Candidate Selection Through AI

AI's impact on HR extends beyond retention to candidate success. Emerging tools are revolutionizing candidate selection by leveraging machine learning to match applicants with roles based on their unique competencies, effectively reducing bias in the hiring process.

Canditech, established in 2019, exemplifies this shift. Utilizing AI to review and optimize interview questions, Canditech ensures reliability and fairness. Assessment templates for personality testing and quantitative reasoning further refine candidate profiles, allowing HR leaders to select the most suitable candidates based on skills rather than traditional markers like educational background.

The integration of AI-enhanced skills-based testing mitigates biases in hiring, enabling HR managers to focus on genuine competencies. This approach transcends conventional markers like university qualifications, fostering a more inclusive hiring process.

Embracing the AI Revolution in HR

In conclusion, artificial intelligence in HR stands as a formidable ally, offering predictive insights that positively impact employee retention and streamlining unbiased candidate selection processes. Beyond operational efficiency, AI contributes to diversity and inclusion by minimizing biases in hiring and promotion narratives.

While acknowledging the limitations of AI, it's crucial to recognize the proactive efforts of AI-enabled technologies to embed safety protocols. Canditech's additional AI processes for interview questions and assessment templates demonstrate a commitment to reliability and fairness. As governance around AI evolves, HR tools are expected to become increasingly reliable and ethically sound, shaping a more promising future for the intersection of technology and human resources.

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