Reframing talent identification as a status-organising process: Examining talent hierarchies through data mining

Sanne Nijs*, Nicky Dries , Veronique Van Vlasselaer, Luc Sels

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

We examine how peers form talent appraisals of team members, reframing talent identification as a status-organising social process. Using decision trees, we modelled configurations of characteristics and behaviours that predicted dominant versus parallel routes to achieving the status of most talented team member. Across 44 multidisciplinary teams, talent status was most often granted to peers perceived as having both leadership and analytic talent; a STEM degree served a dominant signalling function. Where previous studies assumed that degree operates as a specific status characteristic, we show that a STEM degree operates as a diffuse status characteristic, which predicts status in general. We thus discovered that status hierarchies in teams are also based on the type of talent—and not just the level of talent—members are perceived to possess. In so doing, we offer a proof of concept of what we call ‘talent hierarchies’ in teams, for future research to build on.

Original languageEnglish
Number of pages25
JournalHuman Resource Management Journal
DOIs
Publication statusE-pub ahead of print - 2021

Keywords

  • talent management; talent identification; talent hierarchies; status; decision trees, data-mining.

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