Managing by Data: Algorithmic Categories and Organizing

Abstract

Data and data management techniques increasingly permeate organizations and the contexts in which they are embedded. We conduct an empirical investigation of Last.fm, an online music discovery platform, with a view to unpacking the work of data and algorithms in the process of categorization. Drawing on Eleanor Rosch and her colleagues, we link the making of categories with the construction of basic objects that function as key filters or registers for perceiving and organizing the world and interacting with it. In contexts such as the ones we have studied, basic objects are made out of data rather than expert or community-based knowledge. In such settings, basic objects work as pervasive reality filters and as the entities on which other organizational objects and categories are built. As they diffuse, such objects and the categories they instantiate become naturalized, increasingly reconfiguring the social order of organizations and their environments as a data order. Once key organizational activities such as the making of objects and categorizing are rearranged by data and algorithms, organizations can no longer be framed as separate from the technologies they deploy.