Year: 2025
Type: article
Abstract: This qualitative scientific article explores the design and implementation of predictive compensation models in Panamanian organizations, aiming to provide a strategic guide for Human Resources leaders, executives, and compensation professionals. Through semi-structured interviews, the study analyzed perceptions, current practices, and the main barriers companies face when transitioning to data-driven and forward-looking compensation frameworks. Findings reveal an early stage of technological adoption with a reliance on basic tools and traditional approaches, yet a growing openness toward predictive analytics and competency-based compensation models. Key barriers identified include a lack of training, cultural resistance to change, and budgetary constraints. Nevertheless, participants acknowledged substantial benefits such as improved talent retention and fairer reward systems. The study proposes the Reward Blueprint as an adaptive and transformative model that integrates principles of equity, behavioral economics, total rewards, and strategic talent management. This framework aligns incentives with the real motivations of emerging talent and enhances organizational competitiveness in dynamic environments.
Language: English
Topic: AI and HR Technologies
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7065383203
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