Evidence index
Journal commentary · 2023

What does Sackett et al. (2023) say about designing a selection process?

A 2023 follow-up drawing out what the revised validity estimates mean in practice. Its central figure: in a six-predictor composite, giving cognitive ability zero weight reduces overall validity from .61 to .56. Under the older estimates the same removal cost .20, falling from .66 to .46.

Citation

Sackett, P. R., Zhang, C., Berry, C. M. & Lievens, F. (2023). Revisiting the design of selection systems in light of new findings regarding the validity of widely used predictors. Industrial and Organizational Psychology, 16(3), 283–300.

Primary source opened and quotes confirmed on .

In its own words

Sackett et al. (2022) identified previously unnoticed flaws in the way range restriction corrections have been applied in prior meta-analyses of personnel selection tools. They offered revised estimates of operational validity, which are often quite different from the prior estimates. The present paper attempts to draw out the applied implications of that work.
Abstract

What it does not say

Each of these is a claim made in this market and attributed to the source above. None of them is supported by it.

Commonly claimed: That cognitive ability testing should be dropped.

The paper prices the choice rather than making it. .05 of validity is a real cost; it is simply far smaller than the .20 the older framework implied, which changes how a validity-versus-adverse-impact trade-off should be argued.

Commonly claimed: That .61 → .56 applies to dropping a test you use on its own.

It is a composite of six predictors. An employer whose entire screen is one cognitive test is not in that arithmetic — removing it there removes the whole predictor, not one of six contributions.

Commonly claimed: That this is a separate finding from the 2022 paper.

It is the same data set read for its applied implications. Cite the 2022 paper for the estimates and the 2023 paper for what to do about them; citing the 2023 figures as a new meta-analysis overstates what was found.

The number worth carrying into a procurement conversation

Convert .05 of composite validity into outcomes and it stops being abstract. At a base rate of 50% and one hire in ten, a composite at .61 produces a success rate of 90.2% among those hired and a composite at .56 produces 87.4% — a difference of under three good hires per hundred.

That is the price of removing the predictor with the largest subgroup differences from a well-built composite. It is a number a buyer can weigh against a named fairness risk, which is a materially different conversation from the one the 1998 framework supported, where the same removal looked like giving up a fifth of the process's accuracy.

Why the framing changed as well as the figures

The older literature tabulated each predictor's incremental validity over cognitive ability, which presumes ability is the anchor everything else adds to. On revised estimates it is not the anchor: structured interviews sit above it, and the composite arithmetic shows it contributing modestly once several other predictors are present.

For anyone designing a screen, that reorders the build. Start from the best-structured interview the organisation can actually run consistently, then add the instrument least correlated with it, and treat the ability test as one contributor to be justified on its own terms rather than as the foundation.

Where this source is used here

These pages argue from the source above. If it is ever superseded, these are the pages that have to change.

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SiddharthanFounder, AssessAll — Bodhih Training Solutions

Founder of AssessAll and of Bodhih Training Solutions, a corporate training company in Bangalore. Works on assessment design, scoring and reporting across hiring, L&D and certification programmes.

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