Human resource plays a critical role in the success of any business. That is why finding and hiring the right people for the team is crucial. However, talent sourcing, onboarding, retention, and management are by far one of the most challenging roles for recruiters and HR personnel. For this reason, businesses are always looking for tools and techniques to improve the process and raise the odds of success. This is where data analytics in recruitment comes into play. Data-driven organizations use data analytics to make well-informed decisions. The same technology can be used in recruiting to minimize common challenges and improve the entire recruitment process. That being said, here is how data analytics is playing a big role in recruiting.
Creating a foolproof hiring strategy
Achieving an organization’s recruitment goals starts with building a robust recruitment strategy. This acts as a guide in every step of the recruitment process.
Integrating data analytics in the process helps recruiters identify bottlenecks in the strategy, which pinpoints areas of improvement for better results.
For instance, if the majority of applicants happen to be of low quality, it could mean that the job description needs to be more precise and targeted. Likewise, analyzing the offer-to-acceptance ratio or applicant-to-interview ratio can unlock valuable insights into different areas such as candidate experience and employee value proposition.
Enhancing candidates sourcing
The quality of the people companies hire depends on the outsourcing process. If the platforms or the process used only attract poor-quality candidates, then it is highly likely that recruiters end up with poor-quality hires. Otherwise, they keep going back to the drawing board, which wastes time and increases the cost of hiring. Data analytics helps businesses improve the candidate sourcing process in several ways. They include:
- Candidates benchmarking – Recruiters can analyze top performers’ data including qualifications and soft skills to determine key performance indicators for the role qualifications and expectations. This can guide them in writing job postings that attract the right people
- Determining the best platforms to search for candidates – After placing the job ad on various job boards, recruiters can analyze the quality and quantity of job applicants from the said platforms. This helps narrow down to platforms that add value, which helps prevent the wastage of resources
Finding the best fit
The overall goal of any recruitment process is to find the right for the company. The right fit will fit in well with the existing team, and the company culture and is likely to be highly engaged with the position and the company. Recruiters can use data analytics to analyze data from resumes such as candidates’ skills, companies, industries, job titles, experiences, and certifications. Data analytics can also use data from personal interactions to read non-verbal cues, or communication data such as if a candidate replied to an email and after how long to gain insights into the personality of an applicant. This data is then compared to the set KPIs for qualification to rank candidates. The process reveals the candidates that show the highest probability to succeed in the role.
However, it is important to avoid data silos and adopt a central and interactive system to ensure complete data sets. This improves the accuracy and predictive power to give better insights. In addition, finding the right people for the job is crucial. Looking into platforms where specific data jobs are posted raises the chances of finding quality data analysts.
Improving employee retention
Retaining employees is another challenge that organizations face. Yet, it is very important in reducing the cost of hiring. Data analytics can step in to determine why employees are leaving or are being poached by competitors. In addition, employee data can reveal employees’ interests and preferences, their capabilities, and more. Armed with this kind of data, organizations gain insights into the best ways to keep employees engaged, hence reducing turnover.
Minimizing hiring biases
Hiring biases hinder a company’s ability to achieve its diversity and inclusivity goals. This denies the opportunity to reap the benefits of a diverse and inclusive workforce. However, recruiters can overcome this using data analytics. Using artificial intelligence tools in the ATS system focuses on factors that affect the job position such as qualification and educational background, eliminating discriminatory information such as gender, religion, and the like. In addition, data analytics can be used to help hiring managers recognize areas in which they may be biased. For instance, analyzing the time each manager spends with men compared to women or other underrepresented groups can give insights on how to improve.
Conclusion
Data analytics is a growing trend that is helping organizations make better business decisions that are backed by facts. In recruitment, data analytics plays a vital role in building a successful hiring strategy. In addition, recruiters can reduce hiring biases, and improve candidates sourcing and filling positions faster with the right fits. Moreover, data analytics gives insights on how best to keep talents engaged, increasing retention while at it.
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ABOUT THE AUTHOR
Amanda Booska
adviser for Marketing
Amanda Booska is an adviser for Marketing. She advises many businesses to create branches such as in France, Italy, Switzerland, and the UK. She has experience working in a range of industries and providing technical support in topics such as business growth, market expansion, and product development. Amanda is passionate about family, languages, traveling, and reading.
