From Taylorism to Algorithmic Management: How Technological Evolution Reshapes Foundational Management Principles

This study traces management’s evolution from Frederick W. Taylor’s early 20th‑century scientific management to the contemporary phenomenon of algorithmic management, probing how technological advancements have fundamentally transformed managerial logic and dynamics. Taylorism emphasized optimizing labor through meticulous time‑and‑motion studies, task standardization, top-down control, and managerial oversight, aimed at maximizing economic efficiency and reducing reliance on worker discretion. In contrast, algorithmic management entrusts managerial functions such as monitoring, performance assessment, scheduling, goal‑setting, compensation, and even dismissal to algorithms and automated systems. Enabled by real‑time data collection, predictive analytics, and digital platforms, algorithmic management enables organizations to manage dispersed labor at scale with unprecedented precision. While both approaches share enduring principles like efficiency, standardization, and control, the shift from human supervision to software‑mediated governance introduces distinctive dynamics. Algorithmic systems create triangular visibility regimes rather than traditional hierarchical oversight, often obscuring decision logic and engendering information asymmetries, where employers and increasingly algorithm designers hold more knowledge than workers do. Moreover, the impacts of algorithmic management are complex and dual in nature. Empirical and theoretical literature suggests such systems can simultaneously restrict and enable worker autonomy and value creation shaping workstation design, job demands, well-being, and motivation. This duality underscores that algorithmic management’s consequences are not predetermined by technology but are contingent on sociotechnical design and implementation choices. The paper explores how these shifts play out in contemporary labor contexts - from gig platforms to fulfillment centers where workers are subject to algorithmic surveillance and quantified performance regimes, compelling new forms of worker resistance, adaptation, and negotiation of agency. Integrating Labor Process Theory, the analysis reveals how algorithmic systems reenact power asymmetries and labor control while posing fresh challenges and opportunities for worker autonomy and organizational justice. It argues that as management becomes digitized, practitioners, policymakers, and scholars must critically assess algorithmic design, prioritize ethical implementation, and craft frameworks to preserve worker dignity, transparency, and fairness.