Do You Need to Run an Adverse Impact Analysis for Every Hiring Round?

Posted on August 11, 2025

Adverse impact analysis helps you spot whether a hiring process disproportionately screens out protected group members, even without intent to discriminate. Calculating adverse impact is a cornerstone of fair hiring because it surfaces hidden barriers in job ads, screening tools, assessments, and interview decisions. Beyond ethics, it supports compliance with equal employment regulations and builds trust with candidates and employees.

So, do you need to run an adverse impact analysis for every hiring round? In many cases, yes—or at least at regular intervals that match your hiring volume and risk profile. The right cadence depends on your industry, company size, and how often you hire. Still, the guiding principle is simple: analyze often enough to catch and correct issues before they become patterns.

What is an Adverse Impact Analysis?

Adverse impact (disparate impact) occurs when a seemingly neutral practice results in a significantly lower selection rate for a protected group than another group. Protected characteristics vary by jurisdiction, but commonly include race, sex, age (40+), ethnicity, disability status, and veteran status.

You’re not looking for intent; you’re looking for outcomes. If your applicant tracking system (ATS) screens out qualified candidates due to keyword bias, or your assessment favors one demographic, you may see adverse impact—often without realizing it.

Calculating Adverse Impact Using the 4/5 (80%) Rule

The 4/5 rule is a practical test used to flag potential adverse impact. It doesn’t prove discrimination, but it signals where deeper review is needed.

Follow these steps for a single hiring round:

1) Define the selection step and period

• Choose the decision point you’re evaluating (e.g., resume screen, assessment pass/fail, final offer).
• Specify the time frame (e.g., one hiring round for Customer Support Reps in July).

2) Identify comparison groups

• Pick a reference group with the highest selection rate (often the majority group in your applicant pool).
• Compare each other’s group to this reference group. Example groups: men vs. women; Group A vs. Group B by race/ethnicity.

3) Calculate selection rates

• Selection rate = number selected / number who applied (or number who reached that stage).
• Example: 40 women applied, 8 were hired → 8/40 = 20%. 60 men applied, 18 were hired → 18/60 = 30%.

4) Compute the impact ratio for each group

• Impact ratio = (selection rate of group) / (selection rate of reference group).

Using the example above, if men are the reference group at 30%: women’s impact ratio = 20% / 30% = 0.67.

5) Apply the 4/5 rule

• If the impact ratio is less than 0.80 (80%), this flags potential adverse impact and warrants further review.
• In our example, 0.67 < 0.80, so you should investigate.

6) Document context and next steps

• Note the stage, data sources, small-sample caveats, and any process differences.
• Plan corrective actions (e.g., revise job criteria, revalidate assessments, retrain interviewers).

Tips for Adverse Impact Analysis:

• Run the analysis at major decision points (screen, assess, interview, offer).
• Use the smallest unit that makes sense: role, department, location, or requisition—depending on sample size.

Common Pitfalls to Avoid When Calculating Adverse Impact

• Small sample sizes: With very few candidates, percentages swing wildly. Use caution when interpreting results below about 30 candidates per group. Consider aggregating similar roles or extending the time window.
• Ignoring intersectionality: Looking only at “women” or “Black candidates” may miss issues affecting specific intersections (e.g., Black women). Where privacy and sample size allow, review key intersections.
• Misclassifying stages: Be consistent about who counts as “applied,” “screened,” “assessed,” and “selected.” Mixing denominators distorts selection rates.
• Missing groups: Don’t analyze only the largest groups. Include all groups represented in your applicant pool, even if their numbers are smaller (noting small-sample caveats).
• Treating 80% as a pass/fail law: The 4/5 rule is a screening tool, not a legal determination. Ratios above 0.80 don’t guarantee fairness; ratios below 0.80 require deeper validation and job-related justification.
• One-and-done reviews: Processes change—job ads, sourcing channels, assessments, and hiring managers vary over time. Periodic review is essential.

Penalties for Noncompliance with the 4/5 Rule and Governing Agencies

Failure to adhere to the 4/5 rule can lead to serious consequences for organizations, particularly if there is evidence of disparate impact or discrimination in hiring practices. Noncompliance may result in investigations, legal action, or financial penalties. Employers may face lawsuits from applicants or employees under Title VII of the Civil Rights Act of 1964, which prohibits employment discrimination based on race, color, religion, sex, or national origin.

Primary regulatory agencies governing adherence to fair hiring practices include the Equal Employment Opportunity Commission (EEOC) and the Office of Federal Contract Compliance Programs (OFCCP). The EEOC oversees non-discrimination rules for most employers, while the OFCCP ensures compliance among federal contractors and subcontractors. These agencies can initiate detailed audits and impose corrective measures or sanctions if an employer’s processes are found to violate anti-discrimination laws.

How Often Do You Think You Should Run an Adverse Impact Analysis?

It depends on your hiring context:

• High-volume hiring (retail, logistics, call centers): Analyze every round or at least monthly. Small biases compound quickly across hundreds of hires.
• Regulated or high-risk roles (financial services, healthcare, defense): Analyze each stage per requisition or quarterly at a minimum. Maintain robust documentation for audits.
• Startup or small company (<100 employees): If hiring sporadically, run analysis per hire for critical roles or quarterly across all hires. Aggregate to reach meaningful sample sizes.
• Mid-size or enterprise (100–5,000+ employees): Set a cadence: monthly for high-volume roles; quarterly for professional roles; per-requisition for sensitive or public-facing positions.
• Seasonal hiring: Analyze pre-season (validate tools), mid-season (spot-check), and post-season (summative review).

The rule of thumb: if you have enough candidates in a round to produce stable rates, analyze that round. Otherwise, aggregate across similar requisitions or time periods.

Practical Steps to Implement

• Standardize data capture: Ensure your ATS reliably tracks application stage, stage outcomes, and voluntary demographic data with strong privacy controls.
• Set clear responsibility: Assign ownership to HR analytics or compliance. Create a playbook for when ratios fall below 0.80.
• Validate tools: Regularly review job requirements, assessments, and structured interviews for job relevance and predictive validity.
• Diversify sourcing: If one channel skews your pool, broaden outreach to improve representation before selection stages even begin.
• Train decision-makers: Teach hiring teams how to use structured criteria and avoid informal shortcuts that can introduce bias.
• Close the loop: When you find issues, document changes and re-test to confirm improvement.

Real-World Examples of Calculating Adverse Impact

1) High-volume retail hiring (large company, fast cadence)

• Context: A national retailer hires 500 seasonal associates in four waves.
• Finding: Wave 1 shows an impact ratio of 0.72 for women at the assessment stage. The assessment prioritized heavy-lifting tasks not essential for all roles.
• Action: Updated the assessment to reflect real job tasks and offered alternative methods to demonstrate capability.
• Result: In Wave 2, the impact ratio improved to 0.92 with no drop in job performance.

2) Tech startup engineering hires (small company, low volume)

• Context: A 60-employee SaaS firm makes 8 engineering hires per quarter.
• Finding: Quarterly analysis across combined requisitions shows an impact ratio of 0.78 for Latino candidates at the resume screen. Sourcing relied heavily on a narrow alumni network.
• Action: Expanded sourcing to community organizations and adjusted the job ad to focus on skills over pedigree.
• Result: The next quarter’s impact ratio rose to 0.88, and interview-to-offer rates held steady.

3) Hospital clinical roles (regulated industry, high stakes)

• Context: A regional hospital fills 120 nurse positions annually.
• Finding: At the final interview stage, candidates aged 40+ had an impact ratio of 0.76. Interviews were unstructured and favored recent graduates with similar training backgrounds.
• Action: Implemented structured interviews with job-related behavioral questions and standardized scoring.
• Result: The impact ratio increased to 0.95 over two quarters, and first-year retention improved by 6%.

Do You Need to Run an Adverse Impact Analysis for Every Round?

If you hire frequently or operate in regulated or high-visibility sectors, yes—run adverse impact analyses each round or at least monthly by role family. For more minor or sporadic hiring, analyze per requisition when numbers allow; otherwise, aggregate by quarter to get stable results. The goal is to detect and correct issues early, protect your organization, and ensure every candidate gets a fair shot.

Adverse impact analysis isn’t paperwork—it’s quality control for hiring decisions. Run it often enough to trust your outcomes.

Contact EQHR Solutions for Guidance or an HR Consultation

For expert assistance, contact EQHR Solutions at 855-461-8808.