Recruitment analytics is defined as the application of statistical and predictive analysis to the recruitment process to improve sourcing, selection and hiring. In essence, recruitment analytics helps HR leaders and recruiters understand the present and future performance potential of their recruitment processes. This enables them to find the answers to critical questions about the recruiting process, such as:
1. Which sourcing channel sources the best candidates?
2. What is the cost of filling a vacancy?
3. How many applications are received per opening?
4. Where is the recruitment full do most candidates drop out
Recruitment analytics accounts for recruitment data from multiple sources and candidate feedback to provide answers to questions about the recruitment process.
Measuring the efficiency and smoothness of the hiring process is certainly an important reason to analyse recruitment data. However, it isn’t the only metric employers should be interested in. Following are the key recruitment analytics metric that employers should be tracking:
1. Source of candidates: which hiring platform is literally sourcing candidates from.
2. Number of applicants: The number of qualified applicants that are there for each job.
3. Time to hire: the length of the hiring process.
4. Cost per hire: The internal and external costs associated with hiring.
5. Qualiy of hire: How does the new hire stack up to previous hires
6. Retention: The retention rate of employees
7. Applicant to hire ratio: How many interview and applicants are needed to fill the role
With access to a robust recruitment analytics system, employers can access data any time at any place to optimize the hiring process.
There are multiple benefits of using recruitment analytics such as better quality of hire, reduced time to hire, improved ROI of the recruitment budget. By using the recruitment metrics in a strategic manner, recruiters will be able to make better hiring decisions.
Recruiters can utilize recruitment analytics to find the right candidate from the initial stages of the recruitment process. By using recruitment tools with machine learning algorithms based on the organisation’s work culture, recruiters can quickly discern if the candidate is the right fit for the company. These hiring algorithms can measure the candidate’s soft skills and predict turnover risk. After predicting such useful information, recruiters can easily shortlist prospects and process to the next round of interviews.
Candidate sourcing is one for the most time consuming part of recruitment. Recruitment analytics can help recruiters optimize their hiring strategies by removing poor or ineffective sourcing channels. The reports provided by recruitment analytics will help recruiters evaluate the efficacy of job boards. By identifying the best sourcing channels with the help of recruitment analytics, recruiters can get better returns on their job advertising budget, get more competent hires, and improve the quality of hire.
One of the most important abilities recruiters can acquire with recruitment analytics is gaining insights into upcoming industry trends. Data can help recruiters get a better understanding of demand and supply dynamics in the job market, which can then guide them in redefining their hiring strategy for better efficiency and outcomes.
Cloud-based HR analytics solutions offer end-to-end solutions to help recruiters money the entire recruiting pipeline, identify blockers, enables them to hire better and faster, and be ahead of the curve in recruitment practices. However, recruiters must be mindful to remember that recruitment analytics isn’t just a one-time affair. In order to make the recruitment a success, recruiters must continuously strive to improve hiring processes. With he power of recruitment analytics, they can assess and double down on their company’s strengths and eliminate weaknesses so that they can fulfil the talent needs of the organization.
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