New Talent Signals: Shiny New Objects or a Brave New World?

Новые сигналы о талантах: блестящие новинки или дивный новый мир?
Tomas Chamorro‐Premuzic, Dave Winsborough, Ryne A. Sherman, R. C. Hogan
2016-05-11

industrial-organizational psychologysmartphone profiling appstalent identificationworkplace assessmentworkplace big data
Almost 20 years after McKinsey introduced the idea of a war for talent, technology is disrupting the talent identification industry. From smartphone profiling apps to workplace big data, the digital revolution has produced a wide range of new tools for making quick and cheap inferences about human potential and predicting future work performance. However, academic industrial–organizational (I-O) psychologists appear to be mostly spectators. Indeed, there is little scientific research on innovative assessment methods, leaving human resources (HR) practitioners with no credible evidence to evaluate the utility of such tools. To this end, this article provides an overview of new talent identification tools, using traditional workplace assessment methods as the organizing framework for classifying and evaluating new tools, which are largely technologically enhanced versions of traditional methods. We highlight some opportunities and challenges for I-O psychology practitioners interested in exploring and improving these innovations.
1
Academic industrial–organizational psychology research has not kept pace with innovative assessment methods, leaving HR practitioners without credible evidence of their utility.
2
Digital technologies are disrupting talent identification through smartphone profiling apps, workplace big data, and inexpensive tools for predicting work performance.
3
Most emerging talent-identification tools are technologically enhanced versions of traditional workplace assessment methods.
4
The innovations create opportunities for I-O psychologists while also presenting challenges in validating and improving their practical use.
5
Traditional workplace assessment methods provide a framework for classifying and evaluating new talent-identification technologies.

new technology-enabled talent identification and workplace assessment tools

their utility, classification, and credibility for inferring human potential and predicting future work performance

Publication Details
Publication Date
2016-05-11
Journal
Publisher
ISSN
Access Type
Author Information
Authors
Tomas Chamorro‐Premuzic
Dave Winsborough
Ryne A. Sherman
R. C. Hogan
Explore further
Open the scid.ai AI chat with a ready-made request: it will find papers on a similar topic and help build a literature review.
Find similar papers in the chat
Make a presentation
100%