The adverse impact ratio is a number that compares how often one demographic group makes it through a hiring, promotion, or termination process against the group with the best success rate. You calculate it by dividing the selection rate of the group in question by the selection rate of the most-selected group. If the result falls below 0.80 (the four-fifths threshold), federal enforcement agencies will generally treat it as evidence that the practice may be screening out a protected race, sex, or ethnic group in violation of Title VII of the Civil Rights Act of 1964.1eCFR. 41 CFR Part 60-3 – Uniform Guidelines on Employee Selection Procedures (1978) – Section 60-3.4
The ratio doesn’t prove anyone intended to discriminate. It flags a statistical pattern that triggers a closer look.
How to Calculate It
You need two numbers for each group: how many people applied (or were considered) and how many were selected. Divide selections by applicants for each group. That gives you a selection rate. Then find the group with the highest selection rate and use it as your benchmark. Every other group’s rate gets divided by that benchmark. The result is the adverse impact ratio for that group.
Here is what that looks like with real numbers. A warehouse receives 200 applications: 120 from men and 80 from women. It hires 60 men and 24 women.
- Men’s selection rate: 60 ÷ 120 = 0.50
- Women’s selection rate: 24 ÷ 80 = 0.30
Men have the higher rate, so they are the benchmark. Divide 0.30 by 0.50 and you get 0.60. That’s well below 0.80, which means the hiring process shows adverse impact against women.1eCFR. 41 CFR Part 60-3 – Uniform Guidelines on Employee Selection Procedures (1978) – Section 60-3.4
Run the same calculation for every demographic group you tracked. Each racial group gets compared to whichever racial group had the highest selection rate. Sex is compared separately from race. You end up with a separate ratio for each protected-group comparison.
Layoffs and Terminations Flip the Direction
The same math applies to negative actions like layoffs, but you’re now measuring who gets selected for termination rather than for a job. When you compare a group’s termination rate to the group with the lowest termination rate, the warning threshold is 1.25 (the mathematical inverse of 0.80). A ratio above 1.25 signals that the group is being terminated at a disproportionate rate. The underlying question doesn’t change: is the gap between rates small enough to be random, or wide enough to demand an explanation?
Why 0.80 Isn’t a Verdict by Itself
The four-fifths rule is a screening device. A ratio above 0.80 doesn’t guarantee compliance, and a ratio below it doesn’t conclusively prove discrimination. The Supreme Court has called it a “rule of thumb,” and courts routinely layer more statistical analysis on top of it.
The reason is sample size. Hiring five people from a pool of twelve produces a ratio, but that ratio tells you almost nothing statistically. Small pools swing wildly on chance alone. That’s why courts and agencies pair the four-fifths ratio with significance testing. The Office of Federal Contract Compliance Programs will pursue enforcement only when the disparity is statistically significant at a 95 percent confidence level (about two standard deviations) with supporting nonstatistical evidence, or at 99 percent (about three standard deviations) when the statistical evidence stands alone.2Federal Register. Nondiscrimination Obligations of Federal Contractors and Subcontractors Procedures To Resolve Potential Employment Discrimination
The larger the applicant pool, the more the ratio actually means. With fewer than about 30 applicants in a group, most statisticians treat any ratio with serious skepticism. A 0.60 ratio drawn from 500 applicants is a real problem; the same 0.60 drawn from 15 applicants may be noise.
What Happens When the Ratio Fails
Title VII lays out a three-step process once a disparity shows up. Each step shifts the burden between the parties.
The Employee Points to a Specific Practice
The person challenging the practice has to identify what caused the disparity. Not the general shape of the workforce, but a specific requirement: a fitness test, a degree requirement, a credit check, an algorithmic screener. Then they show the statistical gap that practice produces.3Office of the Law Revision Counsel. 42 US Code 2000e-2 – Unlawful Employment Practices If the selection process is so tangled that individual pieces can’t be separated for analysis, the whole process can be challenged as one practice.
The Employer Proves Business Necessity
Once the plaintiff makes that showing, the employer has to prove the challenged practice is job-related and consistent with business necessity.3Office of the Law Revision Counsel. 42 US Code 2000e-2 – Unlawful Employment Practices The Supreme Court set that standard in Griggs v. Duke Power Co. in 1971, holding that employment practices fair on their face but discriminatory in operation are prohibited unless the employer can show a demonstrable relationship to job performance.4Justia US Supreme Court. Griggs v Duke Power Co 401 US 424 (1971)
In practice, meeting this burden usually takes a validation study showing the requirement actually predicts success in the job. A warehouse requiring applicants to lift 50 pounds can point to documentation that the work regularly involves lifting that weight. An office demanding a bachelor’s degree for a data entry role will struggle to show the degree predicts performance.
The Employee Offers a Less Discriminatory Alternative
Business necessity doesn’t end the case. The plaintiff can still win by identifying an alternative practice that meets the employer’s legitimate needs while producing less adverse impact. If the employer refuses to adopt it, the original practice becomes unlawful.3Office of the Law Revision Counsel. 42 US Code 2000e-2 – Unlawful Employment Practices If a typing test screens out a protected group but a structured work sample predicts performance equally well with a smaller gap, the employer may be required to switch.
Many employers stop analyzing at step two. That’s where cases get lost.
Algorithmic Hiring Tools
Resume screeners, video interview scoring, and ranking algorithms sit inside the same framework as a paper test. If the tool’s selection rate falls below 0.80 for a protected group, the employer faces the same burden-shifting sequence.
The EEOC has said employers remain responsible for discriminatory outcomes even when a third-party vendor built and runs the software. Outsourcing the screening does not outsource the liability. If a vendor’s model disproportionately filters out applicants of a particular race or sex, the employer using it can be held liable under Title VII.
The practical response is to demand adverse impact analyses from vendors before deployment and then run your own on live applicant data once the tool is in use. Discovering a 0.55 ratio after a complaint arrives is expensive.
Records You Need to Keep
The analysis only works if the underlying data is reliable. Federal regulations require employers to keep records showing the impact of their selection procedures on each identifiable race, sex, or ethnic group.5eCFR. 29 CFR Part 1607 – Uniform Guidelines on Employee Selection Procedures – Section 1607.4 That means tracking applicants at every stage where people get screened out: initial review, assessments, interviews, background checks, final selection.
Personnel and employment records (applications, test results, documentation of hiring, promotion, and termination decisions) must be preserved at least one year from the date the record was made or the action was taken, whichever is later. For involuntary terminations, the year runs from the termination date. Once a discrimination charge is filed, all records relevant to the charge must be kept until the matter is fully resolved.6eCFR. 29 CFR 1602.14 – Preservation of Records Made or Kept
Larger employers also have to maintain validity evidence for any procedure that produces adverse impact.
What Enforcement Can Cost
When the EEOC or a court finds unjustified adverse impact, remedies can include court-ordered changes to hiring practices, back pay for affected people, and compensatory damages for job search costs and emotional harm. Punitive damages are available in cases showing intentional indifference to employees’ rights.
Combined compensatory and punitive damages are capped by employer size:7Office of the Law Revision Counsel. 42 USC 1981a – Damages in Cases of Intentional Discrimination in Employment
- 15 to 100 employees: $50,000 per person
- 101 to 200 employees: $100,000 per person
- 201 to 500 employees: $200,000 per person
- More than 500 employees: $300,000 per person
Back pay isn’t capped. In a hiring case with hundreds of affected applicants, back pay alone can far exceed the per-person damage limits. Federal contractors face an additional risk: the OFCCP can debar them from future government work, and for many contractors that sanction is heavier than any court award.