Recruitment analytics is the discovery and interpretation of meaningful patterns for sourcing, selecting, and hiring. This means that data is used to find and explain patterns in data. For example, if new hires leave within the first three months, this may indicate a mismatch with the job description and the actual role, selection mistakes or a bad onboarding process. This is an example of recruitment analytics.
Process:
Gather performance data
With so much data to keep track of and less time than ever to analyze it, data-based recruiting helps make every hire count. Optimize your candidate hiring process by calculating and tracking key recruiting performance indicators (KPIs) like time-to-fill, time-to-hire, age-of-job, and offer acceptance rate straight from your recruitment KPI dashboard.
Streamline your sourcing with Source Boosters
Having an idea about what type of candidate you’re looking for is work half done. A big part of the job is discovering where to identify great talent. With Source Boosters, you can set a physical location based on a radius search and instantly find talent by job title, skills, and more. Streamlining your sourcing with the help of data ensures better quality hires while saving significant amount of time.
Identify sources for the best candidates
Make the most of every penny you spend with our recruitment analytics software. Monitor the status of your job opening, track how many quality hires you’re getting from each source, identify which sources have the highest turnover rate, and much more. Use recruitment analysis dashboard to learn where your best performers found your job listing so you can focus on that source and drop ones that aren’t working well. Make your recruitment process more cost-effective using actionable insights with recruitment analytics tools.
Recruitment dashboards to attain great hires:
- Time to hire: The time it takes to identify and recruit a candidate to fill a vacant position.
- Time to fill: The time it takes to fill vacant positions.
- Source of hire: Identify which hiring source you use to give you the highest returns
- Cost per hire: Amount spent by your organization to acquire a candidate
- Candidate experience: How candidates feel about your company once they experience your hiring process.
- Offer acceptance rate: Compares the number of candidates who have presented an offer versus the number of candidates who accepted the offer.
- Age of job: The time period of an open job.
Various recruitment metrics
- Time to hire: The time it takes to identify and recruit a candidate to fill a vacant position.
- Time to fill: The time it takes to fill vacant positions.
- Source of hire: Identity which hiring source you use to give you the highest returns
- Cost per hire: Amount spent by the organization to acquire a candidate
- Candidate experience: How candidates feel about the company once they experience your hiring process.
- Offer acceptance rate: Compares the number of candidates who have been presented with an offer versus the number of candidates who accepted the offer.
- Age of job: The time period of an open job.
- First-year attrition: Candidates who leave in their first year of job fail to become productive and usually cost a lot of money.
- Quality of Hire: An indicator of the first-year performance of a candidate.
- Selection Ratio: The selection ratio usually refers to the number of hired candidates compared to the total number of candidates.
- Selection Channel Effectiveness: The ratio percentage of applications with the percentage of impressions of the positions.
Different Analytics:
Level 1: Operational reporting
In level 1, recruitment analytics is descriptive. They represent the well-known core recruiting metrics. Metrics include the cost of hiring, source of hire, applicants per job opening, selection ratio, time to fill, time to hire, hiring manager satisfaction, and more.
Level 2: Advanced reporting
Level 2 represents advanced reporting. Reporting on these measurements still doesn’t require advanced statistical tools but it does require the combination of multiple data sources to be generated.
An example is the candidate experience. In order to assess the candidate experience, different phases in the recruitment cycle will have to be mapped and the candidate experience needs to be measured or otherwise collected. This can happen through surveys integrated into the candidate software or through separate questionnaires.
Level 3: Analytics
Level 3 represents strategic and predictive analytics in recruitment. Strategic analytics includes segmentation, statistical analysis, and the development of people models. Predictive analytics involves the development of predictive models and strategic and scenario planning.
An example of strategic analytics is segmentation in job advertising and the deployment of programmatic advertisement. In programmatic advertisement, target groups for a job opening are defined and then targeted through multiple online sources. In this case, the ad spent (per click or per thousand impressions) should be closely monitored and when needed, adjusted. Because of the segmentation, different advertisements can be tested against different job-seeker segments in an effort to optimize conversion and lower cost.