A framework for digital talent assessment: Guidelines and applications. Issue 5 (3rd September 2022) - Stander, Frederick W.; Rothmann, Sebastian; Popov, Vesselin; Sun, Luning
Abstract : Rapid rises in technology and digitisation in Talent Assessment practices have not been met with an equal advance in research, methodology, and rigor as applies guidelines for best practice use. This risks an inevitable quality deficit in the application of these technologies and leave human resource (HR) Practitioners unempowered to optimise the benefits of a democratised assessment environment. Multi-trait multi-method (MTMM) assessment protocols provide for a framework for best use application of emerging digital talent assessment tools. In this synthesis review study, we outline guidelines for use of digital talent management and development tools and propose a range of practical strategies. We conclude by providing a practical framework for occupationally specific competence assessment suggestions for future research.