We’re sharing a nice little blog from our friends over at CEIPAL about how to use data to optimise your talent pipeline
What is recruitment analytics?
Recruitment analytics is making data-driven decisions based on the interpretation of data for sourcing, selection, and hiring. Recruitment analytics enables hiring managers and HR leaders to break down complex past recruitment data into meaningful insights that can be used to predict the hiring future of the organization. In essence, hiring analytics helps recruitment professionals to measure the potential of the hiring business and find answers to questions like:
- What is the most productive source of candidates?
- What is the cost-per-hire?
- How long does it take for a recruiter to fill a vacancy?
- Which vendor is bringing the best candidates?
Why should you care about recruitment analytics?
With jolting economic uncertainties tearing organizations apart, a vast majority of staffing businesses are already relying on data-driven recruiting by using Applicant Tracking Systems and recruitment CRM-like AI tools to predict the future and manage resources better. Almost every midsize-to- large organization is implementing some sort of recruitment analytics to keep a track of real-time correlation between candidate engagement, employee management, etc to analyze attrition rate and employee wellbeing. Recruitment analytics can benefit your organization in multiple ways-
- Improving the quality of hires
- Better sourcing of candidates
- Optimization of hiring cost
- Increase in recruiters’ productivity
- Prediction of future hiring trends
Key metrics to measure
Applicant Tracking Systems (ATS) track all a candidate’s information, including CV, resume, and cover letter, gathered from multiple sources like job boards, social media, search engines, etc. Most organizations use predictive analytics to foresee recruitment trends for the future. Predictive modeling enables recruiters to tap into huge amounts of data and predict the quality of candidates.
The first thing that every hiring manager should understand is that recruitment analytics is a multidisciplinary approach. It includes bringing together data from multiple functions, sources, and stakeholders and implementing multiple tools. When you have your data stack ready, you can decide on the recruitment metrics you are looking for-
- Time-to-hire- The total time to hire a candidate
- Cost-per-hire- The total amount spent by the organization to acquire a candidate
- Quality of hire- Determined by the performance of the candidate in the first year of employment
- Source of hire- The top sources that work for your organization to find the best talent
- Candidate drop-off rate- The number of candidates that drop off during the application process
- Offer acceptance rate- The number of candidates who accept the job offer
- Job fill rate- The ratio of the total number of jobs filled to the total number of jobs assigned.
Focus on actions, not just findings
A positive candidate experience is created by streamlining multiple omnichannel recruitment marketing processes. Recruitment analytics not only shows the source efficiency and data from multiple touchpoints, but it also helps recruitment leaders to identify strengths and weaknesses and then work on them strategically. Recruitment analytics lays the roadmap for your future recruitment goals. It shows exactly what is working and what is not working for your organization. Leveraging the findings of the recruitment data can successfully help your organization to choose wisely and save a significant sum on third-party spending.
