What Type of Data Sources May Organizational Network Analysis Use?


Angela Bailey

Organizational Network Analysis (ONA) is a valuable tool for understanding the relationships and interactions within an organization. It provides insights into how information flows, how decisions are made, and how work gets done. To conduct an effective ONA, it is important to have access to various data sources that can provide a comprehensive view of the organizational network.

Data Sources for Organizational Network Analysis

ONA can utilize different types of data sources to analyze the organizational network. These sources can be both quantitative and qualitative, providing a holistic understanding of the network’s structure and dynamics. Let’s explore some common data sources used in ONA:

1. Organizational Charts

Organizational charts are a fundamental source of data for ONA.

They visually depict the formal structure of an organization, including reporting lines, departments, and positions. Analyzing these charts can reveal information about hierarchical relationships, reporting structures, and formal communication channels within the organization.

2. Email Communication Data

Email communication data is another crucial source for ONA.

By analyzing email metadata such as sender, recipient, timestamp, and subject line, one can identify patterns of communication flow across individuals or groups. This data helps uncover informal networks that might not be evident from formal structures alone.

3. Collaboration Tools Data

Collaboration tools data, such as project management software or internal social networks, provide insights into how employees collaborate on tasks and projects. By examining who works together frequently or who shares resources and knowledge, one can better understand informal collaboration networks within the organization.

4. Survey Data

Survey data allows organizations to gather qualitative information about relationships among employees.

Surveys can capture perceptions of trust, influence, and information sharing, which are vital for understanding the social dynamics within the organizational network. Combining survey data with quantitative metrics creates a more comprehensive analysis.

5. Meeting and Calendar Data

Meeting and calendar data provide insights into who is interacting with whom and how frequently.

Analyzing this data can reveal patterns of collaboration, decision-making, and information sharing. Additionally, it helps identify key individuals who act as connectors or gatekeepers in the network.

6. Performance Data

Performance data, such as sales figures or project outcomes, can be used to understand the impact of network structures on organizational success. By analyzing how performance metrics relate to network connections, organizations can identify bottlenecks or areas where collaboration is crucial for achieving desired outcomes.

Incorporating Multiple Data Sources

Effective ONA often involves integrating multiple data sources to gain a comprehensive understanding of the organizational network. By combining quantitative data from sources like email communication or collaboration tools with qualitative data from surveys or interviews, organizations can create a more accurate picture of their networks.

For example, an organization might discover through email communication analysis that two departments rarely interact despite being connected in the formal structure. To understand why this disconnect exists, they could conduct surveys to gather qualitative insights on perceived barriers or cultural differences.

The Importance of Data Quality

Data quality is paramount for meaningful ONA results. It is essential to ensure that the collected data is reliable, accurate, and representative of the entire organization. Inaccurate or incomplete data may lead to biased analyses and incorrect conclusions about the organizational network.

To improve data quality, organizations should establish clear guidelines for collecting and analyzing data. They should also consider anonymizing data to encourage honest responses in surveys or interviews. Regular data audits and validation processes can help maintain the integrity of the data used for ONA.


Organizational Network Analysis relies on various data sources to understand the complex relationships and interactions within an organization. By using a combination of formal and informal data, organizations can gain valuable insights into information flow, collaboration patterns, and decision-making processes. The effective integration of multiple data sources ensures a comprehensive understanding of the organizational network, enabling organizations to make informed decisions and drive positive change.

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