Machine Learning Based Method for Deciding Internal Value of Talent

Loyarte-López, Edurne and García-Olaizola, Igor (2022) Machine Learning Based Method for Deciding Internal Value of Talent. Applied Artificial Intelligence, 36 (1). ISSN 0883-9514

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Abstract

This paper presents a machine-learning-based method for evaluating the internal value of talent in any organization and for evaluating the salary criteria. The study assumes the design and development of a salary predictor, based on artificial intelligence technologies, to help determine the internal value of employees and guarantee internal equity in the organization. The aim of the study is to achieve internal equity, which is a critical element a that directly affects employees’ motivation. We implemented and validated the method with 130 employees and more than 70 talent acquisition cases with a Basque technology research organization during the years 2021 and 2022. The proposed method is based on statistical data assessment and machine-learning-based regression. We found that while most organizations have established variables for job evaluation as well as salary increments for staff according to their contribution to the organization, only a few employ tools to support equitable internal compensation. This study presents a successful real case of artificial intelligence applications where machine learning techniques help managers make the most equitable and least biased salary decisions possible, based on data.

Item Type: Article
Subjects: Open Research Librarians > Computer Science
Depositing User: Unnamed user with email support@open.researchlibrarians.com
Date Deposited: 14 Jun 2023 12:02
Last Modified: 31 Oct 2023 06:19
URI: http://stm.e4journal.com/id/eprint/1231

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