Organizational Network Analysis
Organizational Network Analysis (ONA) has been a popular people analytics topic for years, I started my journey of study & research, development and application back in 2020, and this is a summary of what I have learned and my work in this area so far.
SO, WHAT’S ONA?
On the left side, there is a traditional organizational chart that depicts groupings and hierarchies. However, in reality, people do not work strictly within these hierarchical structures. Instead, individuals are embedded in multiple overlapping networks, as shown on the right side of the above image. These networks include face-to-face interactions, friendships, advice-sharing, and meeting collaborations. It is through these diverse networks that work is accomplished.
With this in mind, Organizational Network Analysis (ONA) is a method that portrays organizations as a collection of individuals connected to one another through their daily interactions and relationships. This approach recognizes the complexity of organizational dynamics.
The resulting visualization of the network can be subjected to mathematical analysis, revealing various characteristics. By studying the visualization, we can understand how individuals collaborate within the network, the level of collaboration between different teams, and the presence of isolated groups or individual silos. Unlike a traditional organizational chart, the organizational network visualization captures the organization’s actual collaboration patterns and information flow.
Extensive research and real-life cases have demonstrated that ONA provides valuable insights that can unlock innovation, drive productivity, improve performance, and simultaneously enhance employee experience and well-being.
A DEMO
Let me use an example to better explain the concept
Below is a traditional org chart made up for demo purpose, we have one director here and 6 direct reports, and few teams here labeled with different colors
Below graph is the same organization but in a network view. This network visualization was generated through a Python program we developed internally, visualizing the interactions and connections between each individuals of the organization.
Each node within this graph represents an individual within the team. The size of each node corresponds to the volume of connections, collaborations, and information flow that the individual has within the organization. Larger nodes indicate a higher number of connections, collaborations, and information flow, while smaller nodes represent fewer of these interactions.
The lines connecting the nodes vary in thickness, with wider and stronger lines indicating frequent and important connections, while lighter lines represent less frequent, more casual connections that are of lesser significance. This distinction allows us to differentiate the quality and intensity of connections within the network.
Additionally, the graph incorporates color-coded clusters, representing different teams as defined in the organizational chart. This dynamic visualization enables zooming in to examine the internal network within each team, providing insights into the specific connections between individuals.
Through this visualization, we gain a clear understanding of collaborations between individuals and teams, identifying those who work in isolation and those who play crucial roles within the organizational network.
While the visualization is developed using Python, we can enhance it by incorporating additional dimensions to depict various collaboration behaviors. For instance, the visualization below showcases an external case study that incorporates different connection styles (e.g., in person, remote) for Return-To-Work planning purposes.
SO WHAT BUSINESS QUESTIONS ONA CAN ANSWER?
ONA provides a powerful tool for visualizing and analyzing the Organizational Network and its Information Flow, offering actionable insights to support business leaders and HR in addressing various questions, such as:
Identifying Key Individuals and Roles: ONA helps determine the key individuals within the organizational network and understand their specific roles and contributions.
Understanding Daily Operations: ONA enables insights into how the organization functions on a day-to-day basis, including how information flows and how individuals and teams collaborate.
Driving Innovation: ONA assists in identifying individuals who can connect people, stimulate innovation, and exert influence within the network, fostering idea generation and energizing the organization.
Measuring Diversity and Inclusion: ONA provides a unique perspective for measuring initiatives like Diversity and Inclusion (D&I) from a network viewpoint, allowing for different metrics and insights beyond traditional approaches.
Identifying Risk Areas and Weak Links: By examining the network, ONA highlights potential risk areas or weak links where attrition could lead to the loss of critical knowledge and connections within the organization.
Evaluating Organizational Health: ONA helps assess the health of the organization from a network perspective, highlighting issues such as lack of collaboration, burnout among individuals, or underutilization of talent.
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By leveraging ONA, business leaders and HR professionals can gain valuable insights to inform decision-making, drive organizational effectiveness, and address critical challenges within the networked structure of their organization.
UNDERLYING ASSUMPTIONS:
When practicing ONA, there are several underlying assumptions that guide our approach. These assumptions include:
Density as a Key Factor: We recognize that network density plays a significant role. A higher network density indicates a more cohesive organization, leading to increased connections, collaborations, information flow, and knowledge sharing. Ultimately, this results in improved productivity and operational efficiency.
Node Size and Key Roles: In our analysis, we consider the size of nodes within the network. A larger node signifies a key role within the organization, indicating greater reliance on information, possession of social capital, and influence. Individuals in these key roles tend to be better performers and have access to better opportunities. Their contributions are pivotal to overall organizational collaboration, performance, and productivity.
Interpretation and Collaboration: It’s crucial to emphasize that the interpretation and application of ONA require a close partnership between our team and organizational leaders and HR business partners (HRBP). ONA visualizations are not inherently right or wrong, good or bad. They are descriptive tools that require business insights and contextual understanding to be correctly interpreted and effectively applied.
By acknowledging these underlying assumptions and working closely with organizational leaders and HR professionals, we can ensure that the insights derived from ONA are accurately understood and effectively utilized to drive positive organizational outcomes.
DATA COLLECTION
Organizational networks are constructed based on data collected on interactions, relationships, and information flow. This data can be gathered through either passive or active means.
Passive data collection involves monitoring behavior using sophisticated technologies, such as analyzing email traffic using features like Outlook’s Insight functionality. Active data collection, on the other hand, involves directly asking individuals to respond to surveys.
Based on extensive external research and case studies, we have come to the understanding that generating unique insights and actionable recommendations based solely on passive data collection is not the ideal approach. This is because passive data collection, such as tracking emails or meetings through Outlook, does not provide a complete and accurate picture. It fails to capture various channels of connection and collaboration, such as face-to-face discussions, interactions via platforms like WebEx Teams, WhatsApp, phone calls, or WeChat. Additionally, the logic behind Outlook’s insight feature, which considers being copied on an email or being invited to a meeting as indicators of interaction, collaboration, or information flow, may not always reflect the reality of the situation. Passive data collection can often be misleading without the proper context. Therefore, we prefer active data collection methods that put employees in the context and allow us to obtain data directly from them, based on their own judgment and assessment.
It is important to note that we aim to keep the survey process concise to ensure a high response rate, which is crucial for creating a comprehensive network. Too many questions can overwhelm respondents and reduce participation. Furthermore, we have found that a limited number of questions are sufficient for differentiating the levels of collaboration, interaction, and information flow between individuals. After conducting research and pilot studies, we have determined that using just two questions serves this purpose effectively.
Of course depends on the business needs or context we can make finetunes to add more questions and dimensions.
HOW TO READ THE GRAPH?
When analyzing the organizational network graph, several key steps can guide our approach:
High-Level Cluster Analysis: Begin by examining the clusters in the graph from a broader perspective. Observe the distribution patterns of clusters and compare them with the organizational structure. Look for any notable differences or anomalies that may arise.
Individual Focus: Shift the focus to individual nodes within the graph. Identify key individuals based on input from business leaders or other stakeholders who may have a list of key talents in mind. Additionally, pay attention to individuals who may not be on the talent list but are significant within the visualization and cannot be ignored.
Understanding Connections and Density: Gain an understanding of the connections within the network and evaluate the level of density. Note the presence of numerous connections and high density within specific sub-groups. Additionally, assess the extent of connections between clusters or sub-groups, identifying any variations or disparities.
In-Depth Analysis: Delve deeper into the organizational network, examining and measuring it from various perspectives. For example, explore the network’s diversity by assessing the representation and inclusion of different groups within the graph.
By following these steps, we can derive valuable insights from the organizational network graph, allowing us to identify cluster patterns, focus on key individuals, assess connection density, and examine network characteristics from diverse angles such as diversity and inclusion.
To extract actionable insights from the organizational network, it is crucial to incorporate business insights and context into the analysis. When examining individuals and the organization within the network visualization, various observations can be made. For instance, there may be a key talent working in isolation or an individual with significant collaboration and knowledge sharing. It is essential for leaders to verify these findings and form a perspective on whether they align with desired outcomes or not. If there are concerns or issues, further investigation is necessary to understand the underlying reasons and develop appropriate solutions.
Addressing silos within the organization may involve engaging with key talents working in isolation, focusing on enhancing their communication skills, leadership mindset, or considering a potential reorganization. For individuals who play a vital role in connecting people and driving innovation or deliverables, business leaders should explore strategies to retain their contributions.
Similarly, at an organizational level, if collaboration and knowledge sharing are insufficient or if the leadership aims to foster innovation, specific actions can be taken to enhance the cohesiveness of the network and encourage collaboration across different areas, breaking down silos.
Furthermore, metrics already exist that can be leveraged to measure various aspects of the network, such as centrality, density, cohesion, and linkage. These metrics provide quantifiable insights that aid in understanding the network’s dynamics and identifying areas for improvement.
By combining visual analysis with business insights, contextual understanding, and utilizing appropriate metrics, actionable steps can be taken to optimize the organizational network, promote collaboration, and drive desired outcomes.
CONCLUSION:
Working on ONA has been an enjoyable journey. While the logic and technology behind it are straightforward, there is immense untapped potential to explore further. By delving deeper into ONA, we can unlock additional business value, enabling business leaders to gain a deeper understanding of their organizations and make well-informed decisions. This journey of discovery holds exciting possibilities for creating even greater impact and providing valuable insights to drive organizational success.
