We explained in the last blog why Data Science is important. As it is no longer limited to just technology but has extended to recruitment too.
With the boosting economy, there seems to be a swell in employee attrition in the private sector. Thus, organizations end up spending a significant amount of money in hiring and training new employees which isn’t economical.
Various studies suggest that retaining an employee is much more cost-effective than hiring a new one. Hence, there needs to be a solution that can be incorporated into the recruitment system, which can predict if a candidate would be a long term employee in the organization.
This is where Data Science comes into the picture. Using big data analytics in recruitment has better potential to predict successful hires than the old methods.
Data mining helps organizations broaden their horizons to open a larger talent pool, initiate better assessments, predict best hires and estimate the remuneration of the employee.
Why Big Data Analytics In Recruitment Is A Need?
Technology is getting outdated quickly than ever. As we transition from the conventional methods to technological advancements, it is time for the recruitment industry to discard the obsolete methods .
There are over 500 million members on LinkedIn, this means recruiters have millions of resumes at their fingertips. If they abide by their traditional methods, they’ll easily feel exhausted by all this data.
I mean seriously, going through all that data manually results in wastage of precious time. It becomes even more meaningless if the candidate isn’t worth the effort.
This is where Big Data can be fruitful. Let’s understand how it can help.
The five V’s to Big data:
- If big data is a pyramid, volume is its base. The volume of data skyrocketed in the year 2012 for most companies.
- This happened because they started collecting more than three million pieces of data every day. Therefore, when you use big data in recruitment a number of variables come into consideration while selecting a candidate.
- Here’s an example- If you apply big data recruitment for finding a candidate to fill a developer's position, it would look at the candidate’s source code, LinkedIn profile, and other social media channels. Not only this it would also check the websites they visit frequently.
- Along with managing data, the flow of it also matters. It matters to the companies whether the flow of it is as close to real-time or not.
- Velocity is considered more important than volume. As it is better to have limited data in real-time than lots of data and no speed.
- Traditional hiring processes take 29-45 days. This is only an approximate number, some hiring processes can take up to months.
- Therefore, using big data recruiting makes the process more efficient as it recognizes and evaluates information faster.
- This makes sure recruiters reduce the time it takes to research job fit candidates, as they have all the right information.
- Companies obtain data from various sources, from in house devices to smartphone GPS technology or by people’s views on social media.
- This is very helpful in recruitment as it gathers information from a wide range of sources, unlike the traditional methods.
- So, when looking for a candidate as mentioned above it also looks at their source code and social media and combines them both to form a meaningful result.
- In this context, it means accuracy, therefore, does the data received by a company is accurate and has quality?
- With the huge amounts of data received sometimes, there can be trouble in maintaining the quality of it and it could become messy.
- Like: Data in bulk creates confusion whereas less data could convey incomplete information.
- The 5th and most important V stands for value. Bulk of data is of no use to a company if it adds no value.
- However, no data is useful until it is converted into something valuable, i.e. when the right information is extracted from it.
- If a company uses big data for recruitment, they’ll get to know which candidates are better and can spend more time providing them a better candidate experience.
How Big Data Finds Job Fit Candidates?
- It uses the 5 V’s mentioned above, apart from that big data looks at a candidate from various angles and not just from the resume’s perspective. It scans the whole of the internet and combines valuable information on the candidate.
- Big data also emphasizes on the candidates who show expertise in social media like Facebook, Twitter, and show thought leadership by sharing advice and insights on their related industry.
How Does Big Data Add More Value To Resume Screening And Candidate Engagement?
Adds more value to resumes-
- It uncovers and interprets candidate data that it receives from all sources. This helps to understand the true skills of a candidate. Hence finding the best undercover talent for your organization.
- For example- While using big data recruitment, you might find a candidate who skipped college or doesn’t have a fancy brand attached to them. However, they perform and deliver better than the candidates who have both on their resume. Such a talent would turn out to be a great hire.
Adds more value to candidate engagement-
- By using big data recruitment you’ll end up finding some of the best talents and only the relatable ones as per the job role. Which will help you to make their candidate experience better!
- This will give you an edge over your competitors. As you have a great chance to engage with the candidates personally and create these candidates into the promoters of your brand.
Up till now, we’ve talked about how big data analytics in recruitment helps in reducing time to hire, screening the right candidates, and checks all the data related to the candidate. However, there’s more to it.
3 Additional Reasons Why Big Data Is Important-
1. Helps To Identify Hiring Obstacles-
Big data checks your historical patterns of hiring and predicts your future needs. Along with it, it helps you to understand the hurdles in your hiring process. It becomes easier for you to understand the problem when you can locate where in the hiring cycle the candidate drops out.
If you find yourself losing good talent right at the start it means your application process is complicated. Or, if your new hire retention rate is low might be due to a complicated onboarding process.
2. It Interprets Measurable Data-
The difference between traditional HR methods and big data analytics is that you work with evidence-based information. This information can be tracked and measured empirically, unlike before.
This also helps to understand how well the new hiring policies and procedures have been implemented. Rather than abstract context, you will have raw data to back yourself.
3. It Predicts Recruitment Gaps-
Big data helps you to predict gaps in sourcing without it even happens. It helps you forecast potential openings in your organization especially for the roles that are linked to revenue generation.
It compares critical metrics for success against the past hiring trends to understand where do you need to take action to find better candidates.
FUTURE: Big Data In Recruitment
Candidates online will only increase with every passing day. Big data makes sure to monitor, track, and determine exceptional candidates willing to learn new skills.
With candidate information increasing online, it’s just waiting for you to analyze and use it to your advantage. In the beginning, big data recruiting might come across as complicated and unclear.
But, any company can use it to their advantage with very little knowledge of how it works.
Therefore, it is best to invest in new technology and use big data analytics to your benefit. Use, the information available to you for your advantage. Expand your horizon, don’t be stuck with the same shallow candidate pool.