Work

Machine Learning Based Method for Deciding Internal Value of Talent

Year: 2022

Type: article

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.

Source: Applied Artificial Intelligence

DOI: 10.1080/08839514.2022.2151160

Authors: Edurne Loyarte-López, Igor García-Olaizola

Institution: Vicomtech

Language: English

Topic: AI and HR Technologies

Subfield: Organizational Behavior and Human Resource Management

Field: Business, Management and Accounting

Domain: Social Sciences

SDGs: Reduced inequalities, Decent work and economic growth

Open Access status: gold

Estimated APC paid: $2,195