Dynamic Silos: Increased Modularity and Decreased Stability in Intraorganizational Communication Networks During the COVID-19 Pandemic
Year: 2024
Type: article
Abstract: Workplace communications around the world were drastically altered by the COVID-19 pandemic, related work-from-home orders, and the rise of remote work. To understand these shifts, we analyzed aggregated, anonymized metadata from over 360 billion emails within 4,361 organizations worldwide. By comparing month-to-month and year-over-year metrics, we examined changes in network community structures over the 24 months before and after COVID-19. We also examined shifts across multiple communication media (email, instant message, video call, and calendaring software) within a single global organization and compared them with communications shifts that were driven by changes in formal organizational structure. We found that in 2020, organizations around the world became more siloed than in 2019, evidenced by increased modularity. This shift was concurrent with decreased stability within silos. Collectively, our analyses indicate that following the onset of COVID-19, employees’ communications began to shift more dynamically between subcommunities (teams, workgroups, or functional areas). At the same time, once in a subcommunity, they limited their communication to other members of that community. We term these network changes dynamic silos. We provide initial insights into the meaning and implications of dynamic silos for the future of work. This paper was accepted by Lamar Pierce, organizations. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2022.02797 .
Source: Management Science
Authors: Tiona Zuzul, Emily Cox Pahnke, Jonathan Larson, Patrick Bourke, Nicholas Caurvina, Neha Parikh Shah, Fereshteh Amini, Jeffrey Weston, Youngser Park, Joshua Vogelstein, Christopher White, Carey E. Priebe
Language: English
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4401117764