Candidate & Employee Analytics
Analytics over the structured talent data on both sides of the hiring line: Candidate Intelligence profiles the applicant pool in Recruitment, Employee Intelligence profiles the workforce under Employees, and a Human Capital Overview rolls the same picture onto the company dashboard.
CV extraction had already turned unstructured documents into structured talent fields, but nothing read across those records to describe a population.
- Recruiters could not tell how senior, how experienced, or how local the applicant pool was without opening records one at a time
- The same questions applied to existing staff - demographics, seniority, skills, and qualifications had no aggregate view
- Company-level headcount context belonged on the dashboard, not buried inside a module
One analytics approach applied to two populations, reading the same normalized talent schema that CV extraction writes.
- Candidate Intelligence aggregates the applicant pool inside Recruitment, beside Candidate Database and Talent Search
- Employee Intelligence aggregates the workforce under Employees, beside Directory and Employee Documents
- Human Capital Overview surfaces the workforce rollup on the dashboard Daily Overview for company-wide visibility
- Because all three read the extracted talent fields, no separate reporting pipeline was needed
Aggregate panels reported as both count and share of total, covering demographics, seniority, geography, and background.
- Candidate side: experience level, experience year, experience location, current company, applied company, and industry
- Employee side: gender, age split, and nationality across total headcount, plus the same experience breakdowns
- Dashboard rollup adds education background, field of study, skills, languages, and certificates
- Every panel is filterable, so a population can be narrowed before it is read
Turned parsed CVs into a picture of who is applying and who already works here, answerable at a glance instead of record by record.
- Hiring decisions gained pool-level context rather than only per-candidate detail
- Workforce composition - demographics, seniority, nationality, skills - became visible without manual reporting
- Demonstrates the payoff of structured extraction: the same normalized fields serve search, profiles, and analytics