Algorithmic Management as “Taylorism on Steroids”

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Algorithmic Management as “Taylorism on Steroids”

Introduction

In recent years, the rise of digital technology and artificial intelligence has transformed how work is organised, monitored, and evaluated. One of the most controversial developments in this shift is algorithmic management, where algorithms are used to assign tasks, monitor performance, and make decisions traditionally handled by human managers. The Financial Times famously described this phenomenon as “Taylorism on steroids”, drawing a parallel to Frederick Winslow Taylor’s early 20th-century scientific management theory. This essay explores what this comparison means, critically examining how algorithmic management amplifies Taylorist ideas of efficiency and control, and what implications this has for workers and organisations in the modern service sector.

Understanding Taylorism and Algorithmic Management

To understand why algorithmic management is often called “Taylorism on steroids,” it is essential to first understand Taylorism itself. Frederick Taylor’s scientific management theory, developed in the early 1900s, aimed to maximise industrial efficiency through time-motion studies, standardised tasks, and close supervision of workers. Taylor believed that management should control every detail of the work process to ensure maximum productivity (Taylor, 1911).

Algorithmic management applies the same logic but at a far more advanced and automated scale. It uses data analytics, artificial intelligence (AI), and machine learning to track, evaluate, and manage employees in real time. Platforms such as Uber, Deliveroo, and Amazon use sophisticated algorithms to assign work, measure performance, and determine pay—all with minimal human intervention. This digital form of control extends Taylor’s principles by enabling constant monitoring and instantaneous feedback, leading to the “on steroids” description.

For instance, Uber drivers are monitored continuously through the app’s GPS and performance data. The system automatically allocates rides, tracks acceptance rates, and adjusts pay using surge pricing. Similarly, Amazon warehouse workers are guided by handheld devices that assign tasks and monitor completion times to the second. Both examples show how algorithmic systems replicate and intensify Taylor’s emphasis on measurement, standardisation, and efficiency.

“Taylorism on Steroids”: What the Phrase Really Means

The phrase “Taylorism on steroids” captures how algorithmic management amplifies both the power and the reach of Taylor’s scientific management. In traditional Taylorism, managers observed workers and measured output manually. In algorithmic management, data is collected automatically and continuously, often with no human oversight.

Algorithms process vast amounts of information, allowing employers to track everything from productivity and time spent on tasks to even emotional tone in customer service interactions. For example, call centre workers in firms like Teleperformance are monitored by AI systems that analyse voice tone and speed to evaluate politeness and stress levels (Mateescu and Nguyen, 2019). This real-time surveillance would have been impossible in Taylor’s era.

However, while Taylor saw management as a science for improving both productivity and worker performance, algorithmic management often removes worker autonomy almost entirely. It transforms human employees into data points in a digital system, optimised purely for efficiency. This leads to what scholars such as Kellogg et al. (2020) describe as a “data-driven form of managerial control,” where human judgement is replaced by algorithmic logic.

In short, “Taylorism on steroids” reflects the extreme intensification, automation, and depersonalisation of control made possible by modern technology.