Big data and organizational design – the brave new world of algorithmic management and computer augmented transparency

TLDR

Big data and sophisticated algorithms now perform complex tasks—from fraud detection to autonomous driving—and also enable new organizational structures, driving innovation in workplace design. The article proposes a distinction between optimizing‑oriented and open‑ended big‑data systems and explores how each shapes organizational design.

Abstract

Big data and sophisticated algorithms enable software to handle increasingly complex tasks, such as detecting fraud, optimizing logistics routes, and even driving cars. Beyond technical tasks, algorithms enable new ways to organize work. In this article, I suggest a distinction of optimizing-oriented and open-ended systems leveraging big data and examine how they are shaping organizational design. The optimizing-oriented systems, typically based on numerical data, enable smarter control of well-defined tasks, including algorithmic management of human work. Open-ended systems, often based on textual data or visualizations, can provide answers to a broad range of managerial questions relevant to effective organizing, thereby enabling smarter and more responsive definition of tasks and allocation of resources and effort. Algorithms processing conversations that naturally take place in organizations can form 'computer augmented transparency', creating a host of potential benefits, but also threats. These developments are leading to a wave of innovation in organizational design and changes to institutionalized norms of the workplace.