Recruitment Analytics to Improve the Hiring Process
Hiring is a process where you can’t afford to make mistakes. This is why you should make the right decisions while hiring at any cost. When it comes to decision making in any part of a business structure, it is better to put data and analytics to use. Streamlining the hiring process along with improving its quality takes more than just a good hiring team. This is where Recruitment Analytics comes to our rescue.
If you’re new to the term, Recruitment Analytics is all about having a system for tracking, measuring, collating and analysing candidate and employee data to use it in making better hiring decisions. Apart from helping in the recruitment, it also helps you in providing unique opportunities to the existing talent in order to improve employee retention.
Having a Recruitment Analytics system in place can save you a lot of headache as an employer. You might be worried about acquiring the right talent, new hires slipping away or retaining the older ones. Data and predictive analysis has the solutions to all your recruitment related problems. Here are some of the benefits you can reap by ditching the old school techniques of hiring and moving onto data-based recruiting.
Finding the right candidate:
Companies can use data and analytics to spot the best prospective employees from the starting stage of the hiring process. Especially, soft skills are easier to measure using data-backed hiring algorithms tailored to be used around a company’s work culture. This would evaluate the candidate for skills required to excel and grow within your organization. The same data can be used to evaluate a candidate’s turnover risk which can save you precious time wasted on him/her. After shortlisting the prospects using this intelligent Recruitment Analytics system, the company can proceed to the face-to-face interview, which would finally help you pin-point the right person for the job.
If you have been into recruitment for some time, you would already know how to do sourcing best for the kind of talent you are looking for. Predictive analytics takes this to a further level by helping you get more insights based on each resource you use to find candidates. Data can be mined from social media sites, popular job aggregators etc. to find the key things you should be focusing on. This data can also give you insights into candidates’ preferences like physical locations that are most appealing to your prospects. By streamlining your sourcing with the help of data, you can yield better returns in the form of competent hires that can improve the overall quality of your organization while saving you significant amount of time that could have been lost in wrong sourcing.
Gathering performance data:
With the data mining technologies we have at the moment, you can start evaluating the satisfaction levels of new hires from day one. It can give you a live view to see if the new crew, from managers to CEO, are meeting the expected standards in their respective jobs. This can even be used to measure the overall employee engagement, which would give you signals if there is a risk of turnover. This data can help you predict if an employee might become obsolete, burned out or quit. By taking the necessary actions, any of these can be avoided.
Analyse overall recruitment experience:
If you are wondering how the new hires would rate your organization’s training and orientation, data can provide you the answers. Analytics can be used for identifying and communicating flaws in the boarding process to the HR team, thus fixing it up at the earliest. By addressing the issues from the beginning, future instances of the same can be avoided.
Help with profile tuning:
Understanding exactly what type of skills and personalities are required for a job would help the hiring team to evaluate the candidates on the basis of these traits. This would lead to further streamlining and optimization of the process which in turn increases the quality of shortlisted candidates. When done right with the help of data, profile tuning alone can work wonders in your recruiting.
Identify best candidate sources:
Having an idea about what type of candidates to look for is only half the battle won. A bigger part of it lies in identifying where they come from. Use data to find out where your best performers found your job listing and that’s where you should focus more on. This can also be used to identify which sources has the highest turnover rates and much more. By taking actions on the insights gained, your recruitment process can be made cost-effective and efficient while improving the quality of hires. In the end, you should invest more time and efforts in the fruitful sources and drop the ones that aren’t working well for your company.
Analyse market trends
Market trends are one of the most important aspects that you should consider while hiring new talent. Depending on the demand for various jobs in the market at the moment, you can actually tweak your hiring process for improved efficiency. Analysing the market trends can give you insights on what jobs are currently available in the market and what companies are looking for candidates for these roles. If you are a staffing agency, this data can be used for finding potential clients that are very likely to convert. By gathering data from job aggregators, analysing the market trends becomes easier.
By implementing data and predictive analytics in recruitment, the overall efficiency of your recruitment process can be significantly boosted. Not only that, Recruitment Analytics can also help you find the right candidate for the right job who would stick for long enough. It goes without saying that improving the recruitment will have positive effects on the overall quality of your company that would eventually take it to the top line. Tools like Saberr and Talentpool are good places to start with your Recruitment Analysis process. Data required for the analysis can be sourced from dedicated web scraping services that can provide job listings data depending on your requirements.
Stay tuned for the second part of our blog series on how big data will revolutionize the business scene in the near future.
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