What is Recruitment Analytics?
The identification, analysis, and simplification of relevant patterns for sourcing, choosing, and recruiting are referred to as recruitment analytics. This means that data is utilised to discover and explain data patterns. If recruits depart within the first three months, this may imply a mismatch between the job description and the actual position, selection errors, or a poor onboarding process. This is an illustration of recruiting analytics.
**Many questions may be answered by recruiting analytics, including:
Which sourcing channel produces the best candidates?
How much does it cost to recruit someone for a position?
What characteristics do my top applicants share?
Where is my recruitment funnel do the majority of prospects leave?
Being able to answer these questions is critical for improving recruiting decision-making.
What are the essential recruitment metrics?
You may track hiring rates and enhance the whole recruiting process by using recruitment metrics. Consider the following critical metrics:
Time to hire- the time that elapses between an applicant applying for a vacant position and accepting the employment offer.
Time to fill- the time that passes between posting an open position and accepting a job offer.
Source of hire- assists recruiters in determining where prospects discover jobs and which recruiting sources yield the best results.
Cost per hire- the amount a business spends on hiring.
Candidate experience- how candidates feel about the hiring process at a firm.
Offer acceptance rate– the percentage of employment offers accepted out of all offers received.
Job age- The duration of an open position.
There are four levels of Recruitment Analytics.
**Descriptive Analytics examines past data to determine what happened throughout the recruiting process and identify potentially concerning tendencies.
Examples of descriptive analysis include:
- Reports on Trends
- Scorecards with metrics
- Historical patterns
- The scatter plot
**Diagnostic Analytics is more concerned with what caused these troubling recruiting tendencies.
Examples of diagnostic tests:
- Determination of the root cause
- Monte Carlo
- Pattern recognition
- Ad-hoc analysis
**Predictive Analytics identifies the possible consequences and outcomes of these concerning patterns and hazards to the company.
Predictive analysis examples:
- Statistical modelling with several variables
- Trend prediction
- Predictive indicators for forecasting (identified via root cause analysis)
**Prescriptive Analytics assists businesses in determining the best solution for known recruitment risks and overall company objectives.
Prescriptive analysis examples:
- What-if analytics to explore various recruitment situations by adjusting recruiting metrics and methods
- Workforce planning and scenario simulation