Reimagining Merit-Based Analytics in Federal and Corporate Decision-Making

Iqra Hameed

Abstract: The article presents a comprehensive analysis of the transformation of the concept of merit in the context of algorithmization of corporate and public governance. The study is carried out within an interdisciplinary framework that includes the sociology of technology, organizational theory, administrative law, and digital analytics. The analysis is based on current publications addressing the shift from a diploma-centered evaluation model to a skill-oriented system, the spread of automated decision-making systems, and institutional initiatives aimed at data democratization. The focus is on the mechanisms of shifting merit criteria from the individual qualities of employees or officials to algorithmic procedures, metadata on the use of government datasets, and user engagement metrics. Key challenges are examined, including the problem of fairness perception under automation, the balance between decision accuracy and transparency, and inclusivity limitations in engaging different user groups. Particular attention is given to the comparative analysis of corporate hiring practices and government data management platforms, which allows for the identification of common patterns in forming new foundations of accountability and legitimacy. It is demonstrated that sustainable governance of merit is possible only when technical efficiency is combined with institutional normativity and ethical oversight. The article may be useful for researchers in management, digital sociology, law, and political science, as well as practitioners involved in implementing algorithmic solutions in the fields of labor and public administration.

Keywords: merit, algorithmic governance, fairness, data democratization, digital accountability

How to Cite?: Iqra Hameed, "Reimagining Merit-Based Analytics in Federal and Corporate Decision-Making", Volume 14 Issue 8, August 2025, International Journal of Science and Research (IJSR), Pages: 1680-1683, https://www.ijsr.net/getabstract.php?paperid=SR25827164227, DOI: https://dx.doi.org/10.21275/SR25827164227