It started with a problem.
The Scholastic Aptitude Test (SAT), first administered in 1926 by the College Entrance Examination Board, was designed by Carl Brigham, a Princeton psychologist who had worked on Army intelligence testing during World War I. The Army Alpha test, developed during WWI to classify recruits, was one of the first large-scale standardized assessments. The SAT's early design reflected the theory that it measured innate aptitude rather than learned knowledge, making it an instrument for identifying intelligence regardless of educational background. The College Board and Educational Testing Service (ETS, founded in 1947) have since revised and maintained the SAT and developed a range of standardized assessments.
Historical sources below ↓Then something changed.
Standardized tests created a single comparable metric that could be applied across candidates from different schools, regions, and backgrounds. For admissions and hiring decisions, this was an efficiency gain: rather than evaluating each candidate entirely on their own terms, a common score provided a shared reference point. The practical criticism — that tests measure preparation and access to test preparation as much as the underlying aptitude they claim to measure — led to decades of debate about what standardized measures actually assess and whether the efficiency gain justifies the exclusions they create. For businesses, the equivalent question arises in any standardized screening tool.
What a builder can learn.
Our interpretation: standardized assessments are efficient at generating comparable data and prone to measuring what can be standardized rather than what matters most. For a business builder designing hiring or qualification criteria, the question is whether the criteria are measuring the actual performance relevant to the role, or measuring a proxy for performance that is easier to measure but less predictive. The history of standardized testing shows that the thing being measured and the thing that matters are not always the same.
A door still open.
A hypothesis worth testing: if a small business assessed how it currently screens job candidates and asked which screening steps best predicted actual job performance in the first six months, would it find that the most time-consuming screening step was the most predictive — or that a simpler, less commonly used step predicted performance more reliably?
What assessment criteria does your business use to make hiring decisions — and how do you know those criteria predict performance rather than simply being easy to measure?
Follow the evidence.
History is sourced below. Business lessons are editorial interpretations; future possibilities are questions to test, not predictions.
Prepared from primary-source histories. First edition: 25 Sept 2026.