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Executive Summary

Root Cause: Credentials In, Performance Out

$22.4M
Annual opportunity

Acme defines jobs through credentials (inputs) rather than outcomes (outputs) — creating a fundamental mismatch between what they screen for and what drives on-the-job success. This single upstream design flaw cascades across all six dimensions: inflating compliance risk, suppressing candidate quality, driving up recruiting costs, and producing analytics that measure activity rather than outcomes.

37/100— Overall Audit Score
Six-Factor Scorecard

Click any dimension to see the key finding ↓

▼
35

Financial Impact

At Risk
Cost of mistakes, waste & opportunity cost as % of margin

At $159K contribution margin per employee, even a 5% improvement across 240 improvable exempt hires creates $9.5M in annual value. Combined with $6.4M in bad hire costs and $6.5M in recruiting waste, total opportunity is $22.4M annually.

High Impact
▼
46

Legal Compliance

Moderate Risk
Risk assessment per Littler Mendelson EEOC framework

Degree requirements found in 70%+ of postings, including roles where experience could substitute — creates adverse impact exposure under Littler Mendelson framework. Each unnecessary degree requirement narrows your talent pool and increases legal surface area.

High Risk
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36

Selection Science

At Risk
Utilization of best practices per Sackett et al. (2022)

No work sample or cognitive assessments detected. Relying on interviews + credentials, which explain only 18% of performance variance per Sackett (2022). Structured behavioral interviews with validated scoring would more than double predictive validity.

High Impact
▼
42

Process Quality

Moderate Risk
7-Waste (Muda) analysis across hiring workflow

6-stage interview process with 52 engineering roles across 8+ title variations — classic fragmentation waste. Career Hub consolidation could reduce postings by 40% while improving candidate quality through clearer role definition.

Moderate Impact
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36

AI Utilization

At Risk
Follower vs. leader rank in AI-driven hiring

Interview intelligence platform deployed but limited to efficiency (faster screening) rather than quality (better matching to outcomes). AI is speeding up a broken process instead of improving it — classic automation of waste.

Moderate Impact
▼
26

HR Tech Stack

At Risk
Overall system impact on hiring outcomes

Zero quality-of-hire measurement connecting interview scores to on-the-job performance. The single most important metric for hiring improvement doesn't exist. Tech stack manages activity (time-to-fill, volume) but cannot answer "are we hiring better?"

High Impact
Financial Impact — How We Calculated It
Factor 1: Cost of Bad Hires
$6.4M
207 bad hires × $30,900 avg cost
28% of new hires underperform or leave within 12 months. Cost includes recruiting replacement, lost productivity, and onboarding waste.
Factor 2: Recruiting Waste
$6.5M
75% × $8.7M total spend
$8.7M annual recruiting spend. 75% goes to posting, distributing, screening, and processing — activities AI can compress. Only 25% goes to quality improvement.
Factor 3: Better Hire Value
$9.5M
240 hires × $159K margin × 25% lift
240 exempt hires/year could perform at top-25% level. At $159K contribution margin each, a 25% performance lift from better selection = $9.5M in created value.
Total Annual Opportunity
$22.4M
$30,350
Per new hire
1.1%
Of revenue
1.8%
Of gross profit
Priority Actions — Ranked by Impact

Recommended Next Steps

Ordered by importance, urgency, and financial impact
1

Implement Quality-of-Hire Measurement

Connect interview scores to 6- and 12-month performance ratings. Without this, no other improvement can be measured. This is the foundation.

Importance
Urgency
Impact
2

Rewrite Top-Volume Job Postings

Convert Engineering and Sales postings from credential lists to outcome-focused career messaging. 90 postings covering 68% of open roles. Immediate compliance risk reduction + talent pool expansion.

Importance
Urgency
Impact
3

Add Structured Work Sample Assessments

Introduce validated assessments for top-3 role families (Engineering, Sales, Ops). Moves selection validity from 18% to 50%+ per Sackett (2022). Directly reduces bad hire rate.

Importance
Urgency
Impact
4

Consolidate Career Hubs

Reduce 52 engineering postings to ~15 Career Hubs. Eliminates title fragmentation, simplifies sourcing, and improves candidate experience. Apply same model to Sales (38 → ~10).

Importance
Urgency
Impact
5

Redirect AI from Speed to Quality

Reconfigure interview intelligence tools to measure quality signals (behavioral competency scores, outcome alignment) rather than just processing speed. AI should improve who you hire, not just how fast.

Importance
Urgency
Impact
6

Remove Unnecessary Degree Requirements

Audit all postings for credential requirements without job-relatedness justification. Immediate EEOC risk reduction. Opens talent pool to experienced candidates without traditional credentials.

Importance
Urgency
Impact
Job Posting I/O Score — 20 Postings Analyzed

Credential Language vs. Outcome Language

22 /100
Solutions Engineer
15
Principal Sales Engineer
18
Sr. Software Engineer
20
Sales Development Rep
29
Field Account Executive
31
Product Marketing Mgr
36
What this means: Postings scoring below 30 are overwhelmingly credential-focused — degrees, years of experience, certifications — rather than outcome-focused. This filters out high performers who could do the job but lack the "right" resume.