This assessment evaluates talent acquisition maturity across six critical dimensions: sourcing strategy, pipeline management, interview quality, offer competitiveness, candidate experience, and diversity in hiring. It identifies weaknesses in the recruiting engine and routes to specific improvements. [src2]
What this measures: How effectively the organization identifies and attracts candidates through inbound and outbound channels.
| Score | Level | Description | Evidence |
|---|---|---|---|
| 1 | Ad hoc | Post-and-pray only; single job board; no employer brand | All candidates from one channel; no metrics |
| 2 | Emerging | Multiple boards; some referrals; no channel ROI tracking | 2-3 channels with no effectiveness data |
| 3 | Defined | Multi-channel with tracking; structured referral program; employer brand | Source-of-hire tracked; active career page |
| 4 | Managed | Proactive pipeline building; sourcing CRM; data-driven investment | 500+ nurtured candidates; channel ROI drives budget |
| 5 | Optimized | AI-powered sourcing; predictive matching; automated outbound | Sourced candidates 5x more likely to be hired |
Red flags: >80% hires from single source; no referral program; >50% time on inbound screening. [src1]
What this measures: Candidate flow management with visibility into conversion rates and bottlenecks.
| Score | Level | Description | Evidence |
|---|---|---|---|
| 1 | Ad hoc | No structured pipeline; informal tracking | No ATS; different views of pipeline status |
| 2 | Emerging | ATS with basic stages; <60% adoption; no conversion tracking | Candidates fall through cracks; unintentional ghosting |
| 3 | Defined | 100% ATS adoption; passthrough rates tracked; weekly reviews | Stage conversion visible; 24-48h response SLA |
| 4 | Managed | Real-time dashboards; predictive analytics; bottleneck identification | Pipeline sufficiency forecasting; automated alerts |
| 5 | Optimized | AI-driven optimization; predictive fill dates; dynamic rebalancing | 85%+ fill date accuracy; zero candidate neglect |
What this measures: Whether interviews are structured, fair, efficient, and predictive of success.
| Score | Level | Description | Evidence |
|---|---|---|---|
| 1 | Ad hoc | Unstructured; no scorecards; gut-feel decisions | No interview guides; inconsistent evaluation |
| 2 | Emerging | Some structure; scorecards exist but <50% used | Partial guides; no calibration; no training |
| 3 | Defined | Structured with required scorecards; interviewer training; debrief process | 80%+ scorecard completion; annual training |
| 4 | Managed | Quality tracked; interviewer effectiveness measured; bias detection | Quality-of-hire tied to scores; calibration sessions |
| 5 | Optimized | AI-assisted analysis; real-time coaching; predictive models | Interviewer dashboards; validated scoring models |
Red flags: 20+ interviews per hire; no structured scorecards; no interviewer training. [src1, src6]
What this measures: Whether offers consistently convert top candidates with competitive compensation.
| Score | Level | Description | Evidence |
|---|---|---|---|
| 1 | Ad hoc | Offers based on gut feel; no market data; high decline rate | Acceptance rate unknown; no counter-offer strategy |
| 2 | Emerging | Some market data but outdated; 65-70% acceptance | Annual survey; decline reasons anecdotal |
| 3 | Defined | Current market data; 80%+ acceptance; decline reasons categorized | Role-specific data; total comp presented clearly |
| 4 | Managed | Real-time benchmarking; offer modeling; 85%+ acceptance | Dynamic market data; competitive offer tracking |
| 5 | Optimized | Predictive offer optimization; 90%+ for target candidates | AI-optimized offers; personalized total rewards |
What this measures: Quality of the end-to-end candidate journey from first touchpoint through decision.
| Score | Level | Description | Evidence |
|---|---|---|---|
| 1 | Ad hoc | Candidates ghosted; no communication standards; negative reviews | No status updates; 2+ week gaps between stages |
| 2 | Emerging | Some standards but inconsistent; no experience measurement | Auto-reject emails; sporadic updates; no CSAT |
| 3 | Defined | Communication SLAs; status updates; candidate survey deployed | SLA compliance >80%; post-process survey active |
| 4 | Managed | Candidate NPS tracked; experience drives improvements; personalized | NPS >50; quarterly experience reviews |
| 5 | Optimized | Best-in-class experience; AI-personalized journey; rejected join community | NPS >70; rejected candidates become advocates |
What this measures: Intentional, measurable practices for diverse talent pipeline and equitable evaluation.
| Score | Level | Description | Evidence |
|---|---|---|---|
| 1 | Ad hoc | No strategy; no data; biased JDs; homogeneous panels | No diversity data; exclusionary language |
| 2 | Emerging | Acknowledged as important; basic data; sporadic efforts | Some demographic data; no structured approach |
| 3 | Defined | Goals set; pipeline tracked; inclusive JDs; diverse panels required | Stage-by-stage diversity data; panel policy |
| 4 | Managed | Conversion rates by demographic; bias detection; diverse sourcing | Bias detection in scorecards; sourcing partnerships |
| 5 | Optimized | Systemic equity; AI bias detection; transparent outcomes; inclusive experience | Published diversity outcomes; candidate inclusion scores |
Overall Score = (Sourcing + Pipeline + Interviews + Offers + Experience + D&I) / 6| Overall Score | Maturity Level | Interpretation | Recommended Next Step |
|---|---|---|---|
| 1.0 - 1.9 | Critical | TA is ad hoc and reactive — losing candidates and creating risk | Implement ATS; deploy structured interviews; establish sourcing |
| 2.0 - 2.9 | Developing | Basic infrastructure with significant process gaps | Multi-channel sourcing; interviewer training; experience SLAs |
| 3.0 - 3.9 | Competent | Solid function capable of scaling with improvements | Optimize conversion; implement quality-of-hire; employer brand |
| 4.0 - 4.5 | Advanced | TA is a competitive advantage with data-driven operations | AI-powered tools; predictive models; experience excellence |
| 4.6 - 5.0 | Best-in-class | World-class with predictive capabilities and measurable impact | Maintain leadership; innovate; become industry reference |
| Segment | Expected Average Score | "Good" Threshold | "Alarm" Threshold |
|---|---|---|---|
| Startup (10-50) | 1.8 | 2.3 | 1.3 |
| Growth (51-200) | 2.5 | 3.0 | 1.8 |
| Scale-up (201-1000) | 3.2 | 3.6 | 2.5 |
| Enterprise (1000+) | 3.8 | 4.2 | 3.0 |
Fetch when a user asks to evaluate their recruiting process, diagnose slow hiring, understand offer decline patterns, or assess TA readiness for growth-stage scaling.