How is Data Science Shaping Recruitment?
Tags: datascience, discuss, analytics
Published: 2022-07-06 08:33:47

Data science is revolutionising many industries, including recruitment. Data scientists are using new techniques to improve how companies find, screen and hire candidates. The key to this shift is that data science allows recruiters to use technology to improve the hiring process – from job page optimisation to [predictive analytics](https://recruitee.com/articles/analytics-in-recruitment#:~:text=Simply%20put%2C%20predictive%20analytics%20in,could%20happen%20under%20specific%20scenarios).

In this article, we’ll explore how these technologies are revolutionising recruitment and helping companies hire faster with better results at lower costs:

##Job Page Optimisation
On-site job pages are a great source for candidates, but only if optimised. 

###Employee Referral Programs
[Employee referrals](https://resources.workable.com/stories-and-insights/employee-referral-program) are among the best methods for finding new employees because they originate from individuals already employed by a firm and familiar with its culture. 

###Social Media Retargeting Campaigns
Social media [retargeting campaigns](https://info.recruitics.com/blog/3-things-to-consider-when-creating-facebook-retargeting-campaigns) allow companies to show ads to people who visited their website or clicked on links related to jobs at the company—even if they didn’t apply right away. Businesses can use these adverts to serve as a reminder, while also demonstrating perks like flexible hours and paid vacation days that might entice them into applying later on down the line.

##Workforce Planning
[Workforce planning](https://www.netsuite.com/portal/business-benchmark-brainyard/industries/articles/cfo-central/workforce-planning.shtml) is the process of analysing the future needs of an organisation. It is a strategic process that should be a part of overall strategic planning and business continuity management.

Workforce planning concerns human resource, but it also includes broader organisational issues such as:

* How to attract, retain and develop employees capable of meeting current needs
* What size will a team need to be to meet these objectives?
* How much training do they need to perform their jobs effectively?

##Employee Retention
Data science can also be used to understand [employee retention](https://www.fm-magazine.com/issues/2018/dec/using-predictive-analytics-in-employee-retention.html). Why do employees leave? Is it because of the work environment, or a lack of opportunities for advancement? Does their job satisfaction depend on factors that can be measured, such as pay or benefits? Data science can help employers answer these questions and identify where they fall short. Using data analysis to track attrition rates in an organisation over time and figuring out what causes people to leave, helps businesses to create more effective hiring practices and better retain top talent.

##Candidate Sourcing
Recruitment agencies have access to a wealth of information on candidates, including their education and work history, compensation package, and even what they are like as individuals. They also employ techniques such as behaviour-based psychometric assessment. As a result, they can find the candidate that will be a good fit.

Candidate sourcing includes job and social media sites like LinkedIn or Twitter. However, these sources may not provide as much relevant information about candidates as your recruitment agency does because they don’t have access to all the information about potential employees that an in-house recruiter does.

##HR Analytics
HR analytics helps companies identify trends and patterns in their workforce, helping them make better decisions about their workforce and improve its quality.

In today’s digital age, data is everywhere, and [HR analytics](https://www.cipd.co.uk/knowledge/strategy/analytics/factsheet#gref) is becoming a more common part of human resources management and recruitment processes. The popularity of these applications has also created new job opportunities for people who want to use their skills or expertise in this area.

##Predictive Analysis and Machine Learning in Recruitment

###Predictive Analytics
[Predictive analytics](https://www.softwareadvice.com/resources/predictive-analytics-recruitment-hiring/) is another important machine learning application in recruitment. Predictive analytics can predict a person’s behaviour, preferences and many other things. For example, by analysing previous records of candidates hired, companies can predict the likelihood of them leaving if they receive a better offer. Predictive analytics can also determine if a candidate will be successful based on their past performance and personality traits (among other things).

###Machine Learning In Recruitment: Where Is It Going?
With [machine learning](https://www.herohunt.ai/blog/machine-learning-in-recruitment-a-deep-dive) becoming more popular in recruitment due to its ability to process large amounts of data quickly and accurately, it is only a matter of time until more companies start using it more often than not during the hiring process. If this happens, it will change how we hire forever.

##Data science can speed up hiring and cut costs by up to 75%
Data science has helped companies hire faster and reduced the cost of hiring by [as much as 75%](https://ideal.com/ai-recruiting/). Companies are using data science to hire faster by improving the speed at which they can review resumes and shortlist qualified candidates. In addition, companies are using data science to improve the quality of their hires through better screening processes that eliminate unsuitable applicants early on.

However, not everyone trusts it due to its [complexity](https://www.arcticshores.com/insights/data-science-in-talent-acquisition-the-questions-youll-be-glad-you-asked), which may be a bottleneck to implementation. What is clear is that in a working world experiencing huge shifts, big changes are necessary and revolutionary companies are already implementing this. 

By understanding the types of individuals who will perform well in their roles and where to discover them, artificial intelligence and machine learning are revolutionising recruitment. Companies can use these technologies to their full potential to create an even more diverse and inclusive workforce ready for tomorrow’s challenges.