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Communication network dynamics in a large organizational hierarchy

Nathaniel Josephs, Sida Peng, Forrest W. Crawford

TL;DR

This study investigates how a formal organizational hierarchy shapes emergent intra-organizational email communication in a large, real-world company (Microsoft) using May 2019 data for ~241,718 employees and 95.5 million emails. It introduces new reciprocity and distance-based measures (e.g., SRD, DRD) and analyzes within- and between-team patterns, while comparing multiple tree-reconstruction methods against the true hierarchy. The findings show strong proximity-driven communication, a symmetric SRD but asymmetric DRD, and that a maximum spanning tree best captures the hierarchy, challenging agony/distancel-based theories and suggesting more nuanced, small-world communication models. The work highlights limitations (single-month snapshot, incomplete matching) and suggests future directions for time-indexed Bayesian tree models and broader applicability beyond corporate networks.

Abstract

Most businesses impose a supervisory hierarchy on employees to facilitate management, decision-making, and collaboration, yet routine inter-employee communication patterns within workplaces tend to emerge more naturally as a consequence of both supervisory relationships and the needs of the organization. What then is the relationship between a formal organizational structure and the emergent communications between its employees? Understanding the nature of this relationship is critical for the successful management of an organization. While scholars of organizational management have proposed theories relating organizational trees to communication dynamics, and separately, network scientists have studied the topological structure of communication patterns in different types of organizations, existing empirical analyses are both lacking in representativeness and limited in size. In fact, much of the methodology used to study the relationship between organizational hierarchy and communication patterns comes from analyses of the Enron email corpus, reflecting a uniquely dysfunctional corporate environment. In this paper, we develop new methodology for assessing the relationship between organizational hierarchy and communication dynamics and apply it to Microsoft Corporation, currently the highest valued company in the world, consisting of approximately 200,000 employees divided into 88 teams. This reveals distinct communication network structures within and between teams. We then characterize the relationship of routine employee communication patterns to these team supervisory hierarchies, while empirically evaluating several theories of organizational management and performance. To do so, we propose new measures of communication reciprocity and new shortest-path distances for trees to track the frequency of messages passed up, down, and across the organizational hierarchy.

Communication network dynamics in a large organizational hierarchy

TL;DR

This study investigates how a formal organizational hierarchy shapes emergent intra-organizational email communication in a large, real-world company (Microsoft) using May 2019 data for ~241,718 employees and 95.5 million emails. It introduces new reciprocity and distance-based measures (e.g., SRD, DRD) and analyzes within- and between-team patterns, while comparing multiple tree-reconstruction methods against the true hierarchy. The findings show strong proximity-driven communication, a symmetric SRD but asymmetric DRD, and that a maximum spanning tree best captures the hierarchy, challenging agony/distancel-based theories and suggesting more nuanced, small-world communication models. The work highlights limitations (single-month snapshot, incomplete matching) and suggests future directions for time-indexed Bayesian tree models and broader applicability beyond corporate networks.

Abstract

Most businesses impose a supervisory hierarchy on employees to facilitate management, decision-making, and collaboration, yet routine inter-employee communication patterns within workplaces tend to emerge more naturally as a consequence of both supervisory relationships and the needs of the organization. What then is the relationship between a formal organizational structure and the emergent communications between its employees? Understanding the nature of this relationship is critical for the successful management of an organization. While scholars of organizational management have proposed theories relating organizational trees to communication dynamics, and separately, network scientists have studied the topological structure of communication patterns in different types of organizations, existing empirical analyses are both lacking in representativeness and limited in size. In fact, much of the methodology used to study the relationship between organizational hierarchy and communication patterns comes from analyses of the Enron email corpus, reflecting a uniquely dysfunctional corporate environment. In this paper, we develop new methodology for assessing the relationship between organizational hierarchy and communication dynamics and apply it to Microsoft Corporation, currently the highest valued company in the world, consisting of approximately 200,000 employees divided into 88 teams. This reveals distinct communication network structures within and between teams. We then characterize the relationship of routine employee communication patterns to these team supervisory hierarchies, while empirically evaluating several theories of organizational management and performance. To do so, we propose new measures of communication reciprocity and new shortest-path distances for trees to track the frequency of messages passed up, down, and across the organizational hierarchy.
Paper Structure (25 sections, 1 theorem, 24 equations, 13 figures, 2 tables)

This paper contains 25 sections, 1 theorem, 24 equations, 13 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Data
  3. EDA
  4. Email communication network
  5. EI-Index
  6. New Measures of Communication
  7. Sent versus received emails
  8. Reporting distance
  9. Reconstructing the organizational hierarchy
  10. Discussion
  11. Analyses of communication and organizational structure in the Enron corpus
  12. Scale-free analysis
  13. Comparing network summary statistics
  14. Importance in email network
  15. SRD Hierarchical Position
  16. ...and 10 more sections

Key Result

Proposition 1

Let $T$ be a tree. For any $u, v, w \in V(T)$,

Figures (13)

  • Figure 1: (Left) The organizational tree consisting of 196,832 employees in May 2019. The nodes are colored by team on a gradient such that teams in the same division are closer in color. The CEO is the black dot from which all of the black edges emanate. (Right) The email network consisting of all employees in May 2019 and the 24.6 million edges representing 84.7 million emails using the same color scheme for teams. Edges are directed and colored by source team. For visualization purposes, the email network has been coarsened as described in the text.
  • Figure 2: (Top) Left: Frequency of communication within different groups in the organization. Middle: In-degree and out-degree distributions. Right: In-strength and out-strength distributions. (Bottom) Right: Bivariate (in vs out) degree and strength distributions. Middle: Distribution of EI-index across (and colored by) teams, where the vertical line represents the entire organization's EI-index. (Left): Distribution of weighted EI-index across teams.
  • Figure 3: Measures of team-level email communication and reciprocity by organizational position. (Top) Total degree and strength in the entire email network by relative position in the organization. (Bottom) Left: Difference in the proportions SR and RR by relative position in the organization hierarchy. Right: Difference in the signed proportions SP and RP by HP. In all of the plots, we bin position into 10 equal groupings and we show the box plot within each bin along with a smoothed curve (blue) of the individual (non-binned) data.
  • Figure 4: Pairwise reporting distances in the organizational tree and the average number of emails among all pairs in that reporting distance. Reporting distances are computed within each team and the box plots summarize the results across all of the teams. The individual team plots are shown in Appendix Figure \ref{['fig:eda_path_team']}.
  • Figure S1: Scale-free analysis from broido2019scale performed on the team level.
  • ...and 8 more figures

Theorems & Definitions (2)

  • Proposition 1
  • proof