Organizational Network Analysis

The org chart shows who reports to whom, but it says little about how work actually happens. In practice, people go to trusted colleagues for advice, rely on a few connectors to get things done across departments and avoid certain teams because working with them is slow. These informal networks often matter more to performance than the formal structure. Organizational network analysis makes them visible. By mapping who communicates with whom, who people go to for information and where collaboration breaks down, it shows leaders the real shape of their organization.

Network analysis has roots in sociology, including Jacob Moreno's sociograms in the 1930s, and was brought into management practice by researchers such as Rob Cross, whose work showed how a small number of people often carry a disproportionate share of collaboration. Organizational network analysis now uses surveys and, increasingly, passive data from email, calendars and collaboration tools to map relationships at scale. For organization designers, HR and people analytics teams, change leaders and executives, it provides a view of the organization that no reporting line can show.

Definition of Organizational Network Analysis

Organizational network analysis is a structured method for collecting data on relationships, such as communication, collaboration, advice and trust, among people or groups, then using network mapping and metrics to identify patterns, key individuals, bottlenecks, silos and opportunities to improve how the organization works.

It complements the formal view in an org chart, is a common technique in people analytics and informs organizational design decisions.

Data Collection Methods

Active ONA uses surveys asking people whom they go to for information, advice, decisions or support.

Passive ONA analyzes metadata from email, calendars, chat and collaboration tools to see communication patterns, usually without reading content.

Many organizations combine both, using passive data for scale and surveys for the quality and purpose of relationships.

Privacy safeguards, such as aggregation, consent and limits on individual reporting, are essential with either method.

Key Network Roles and Metrics

Central connectors are people many others rely on, often essential to getting work done and at risk of overload.

Brokers connect otherwise separate groups, carrying information across boundaries.

Peripheral people have few connections, which may signal new joiners, isolated experts or disengagement. New joiners who stay peripheral after several months are at higher risk of leaving, which makes onboarding a common use of network data.

Network metrics include centrality, density within groups and the strength of connections between groups. Patterns over time matter too, since a team whose external connections are shrinking may be becoming isolated.

Importance of Organizational Network Analysis in Workforce and Operations

ONA reveals how work really flows. It shows where collaboration happens and where it is missing, which helps target improvements.

It identifies critical people. Central connectors and brokers often hold knowledge and relationships that the organization would struggle to replace.

It also supports change and integration. Mapping networks helps leaders spot influencers who can spread change and gaps that need bridging after a merger or reorganization. Research by Rob Cross and colleagues found that a small share of employees often accounts for a large share of valuable collaboration, which makes those people both critical and at risk of burnout.

Organizational Network Analysis and Financial Management

Identifying collaboration overload helps reduce time lost to excessive meetings and requests, which carries a real cost in productivity.

Knowing which people are central to key processes helps target retention spending where losing someone would be most costly.

Network data can inform where to place shared resources and how to size teams, avoiding duplicated effort.

Measuring collaboration before and after a reorganization shows whether the change delivered the intended benefits.

Common Challenges

Employees may see passive data collection as surveillance, damaging trust if it is not handled transparently.

Network maps can be misread, for example by treating highly connected people as high performers when they may simply be overloaded.

Survey-based ONA depends on high response rates, since missing responses leave gaps in the network.

Insights can be hard to act on without clear ownership and follow-up. Networks also change quickly, so a single snapshot may not reflect how the organization works a year later.