Data analytics plays an important role in recruitment when it comes to making decisions in the sourcing, selection and onboarding process. Data analytics includes the collection and interpretation of the data that are collected from the profiles of the candidates. The analytics help recruiting managers make data-driven choices in selecting candidates. Recruitment dashboards and applicant tracking systems are one of the major data analytics to collect, interpret and optimize the data. The use of data analytics makes it easier to evaluate the bottlenecks and provide insights into the recruitment process. Predictive analytics such as machine learning and artificial intelligence have made their way into recruitment to leverage present and previous data to analyse trends, behaviour and outcomes of the hiring process.
Levels in recruitment analytics
When you go through the recruitment analytics, there are three levels that we can consider. The labels are operation reporting, advanced reporting and analytics that are dependent on the HR analytics maturity models. Operation reporting is dependent on ATS software and recruitment dashboards. Various advanced reporting is based on financial data of the hiring process. It is conducted through surveys and questionnaires that are Integrated with software. The third level is incorporating predictive analytics such as AI(artificial intelligence), and ML(Machine learning).
Some effective recruitment analytics are customer relationship management systems satisfaction service applicant tracking systems brand data human resources information system (HRIS) data collected from branding and advertisement.
Benefits of data analytics
Avoiding hiring bases
Data analytics in the recruitment process has reduced the hiring biases that allow a company to get skilled employees. Data-driven recruitment encourages making data-driven decisions by analysing the potential employees’ qualifications and skills. AI-driven technology is the most effective data even analytics that can help to screen the profiles of the candidates and shortlist candidates and make a talent pool. DataAnalytics also help to understand the demographics of the organisation and encourage diversity in the workplace.
Evaluating applicant to interview ratio
Applicant to interview ratio is the number of candidates applying for a particular position to the number of candidates interviewed for that. Evaluating the applicant-to-interview ratio gives an insight into the qualities and skills to look for in a potential employee. ATS software and pre-assessment tools can help to analyse the skills and patterns and enriches the hiring process.
The offer to acceptance ratio is about the number of candidates offered for the particular position to the number of candidates accepted for that position. Recruiting managers should redefine and revamp employee value proposition if the rejection rate of offerings is more than the acceptance rate.
KPI is an important data analytics tool that can measure the performance of processes. It brings light on improvement areas and shows the “value and return on investment” for a specific recruitment process. You can use the insights taken from the recruitment KPI to align your business outcomes with the recruitment funnel. KPI is more effective in terms of showing qualified candidates who will be beneficial to meeting business goals.