Academic Journal

Cut to the Curve: Underrecognition and Talent Loss from Forced Ranking in a Multinational Firm.

Bibliographic Details
Title: Cut to the Curve: Underrecognition and Talent Loss from Forced Ranking in a Multinational Firm.
Authors: Bond, Brittany M.1 (AUTHOR) bbond@cornell.edu
Source: Management Science (INFORMS). Apr2026, Vol. 72 Issue 4, p3487-3507. 21p.
Subject Terms: *Employee retention, *Labor turnover, *Employee reviews, *Employee motivation, *Job performance, *International business enterprises, *Organizational behavior, *Organizational justice
Abstract: This paper examines unintended consequences of enforcing a curve on performance rankings. I examine a multinational company where some employees are downgraded from the top levels of rankings due to a strict recognition cutoff. I show that downgraded employees are at least 34% more likely to voluntarily exit, and that attempts by the organization to manage employee concerns, particularly regarding concerns of fairness, envy, and self-image, do not have the intended retention effect. Underrecognized employees leave even though the organization avoids calibration bias, offers reassurance about their career prospects, and compensates them with larger bonuses than their top-ranked peers. In robustness checks, I show that under these conditions even high-performing employees not nominated to the top ranks are more likely to voluntarily depart despite receiving the largest bonuses. These findings suggest that, where underrecognition occurs due to the restriction of top rankings, the mechanisms producing demotivation are more powerful than the management strategies meant to combat them. This paper was accepted by Lamar Pierce, organizations. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2023.01204. [ABSTRACT FROM AUTHOR]
Copyright of Management Science (INFORMS) is the property of INFORMS: Institute for Operations Research & the Management Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Business Source Index
Description
ISSN:00251909
DOI:10.1287/mnsc.2023.01204