1. Introduction to Organizational Network Analysis (ONA)

Definition and Concept

Organizational Network Analysis (ONA) is a structured, data-driven methodology that examines the relationships and flows of information, resources, and influence within an organization. Rather than focusing solely on formal hierarchies or job titles, ONA provides a lens through which the informal dynamics of collaboration, communication, and trust can be understood. It maps how individuals and groups interact in reality—not just how they are supposed to, according to organizational charts.

By studying the patterns of connections among employees, ONA helps uncover the true structure of an organization. It identifies influencers, gatekeepers, and isolated individuals, thereby offering a nuanced picture of how work actually gets done. These insights are vital for organizations aiming to foster innovation, improve performance, or navigate complex changes such as restructuring, mergers, or cultural transformations.

Evolution and History

The foundations of network analysis stem from the field of sociology in the mid-20th century. Early work by researchers like Jacob Moreno, who developed sociograms to visualize interpersonal relationships, laid the groundwork for modern network science. Over time, these ideas evolved into more mathematically rigorous approaches with contributions from graph theory and systems science.

In the 1980s and 1990s, the concept of social networks gained traction in organizational studies, particularly in understanding knowledge flow, leadership dynamics, and innovation diffusion. With the digital transformation of workplaces and the advent of sophisticated analytics tools, ONA emerged as a formalized practice in the 2000s. Today, it's widely used by HR professionals, organizational development consultants, and data scientists to diagnose organizational health and plan strategic interventions.

Importance in Modern Organizations

In today’s volatile, uncertain, complex, and ambiguous (VUCA) business environment, traditional command-and-control structures often fall short of capturing the dynamic ways people collaborate. Work is increasingly project-based, cross-functional, and virtual—making it essential to look beyond static org charts.

ONA is crucial for several reasons:

• Enhancing Collaboration: It helps identify where silos exist and how they can be broken to improve cross-functional teamwork.
• Driving Innovation: ONA reveals informal leaders and knowledge hubs who drive creative problem-solving.
• Navigating Change: Organizations use ONA to understand potential resistance points or leverage influencers during transformation efforts.
• Boosting Engagement: By spotlighting disconnected individuals or teams, ONA aids in crafting better inclusion and engagement strategies.

In essence, ONA offers a real-time, evidence-based approach to understanding and optimizing the inner workings of an organization.

2. Understanding Formal vs Informal Organizational Structures
What is Formal Structure?

The formal organizational structure is the officially sanctioned hierarchy that defines roles, responsibilities, and reporting relationships within an enterprise. This structure is typically documented in an organizational chart and aligns with job titles, departments, workflows, and policies. Formal structures are essential for regulatory compliance, accountability, and operational efficiency.

Examples include:

• Departmental hierarchies (e.g., marketing, HR, finance)
• Reporting lines (e.g., team leader to manager to director)
• Standard operating procedures and communication protocols

However, while the formal structure provides clarity and order, it often fails to capture the nuanced social dynamics and unofficial networks through which much of the real work happens.

What is Informal Network?

An informal network consists of the unofficial, naturally formed relationships among individuals in an organization. These connections emerge from shared interests, friendships, mutual trust, or frequent collaboration. Unlike formal structures, informal networks are not recorded in organizational charts but are immensely powerful in shaping behavior, decision-making, and information flow.

Informal networks can span across teams, departments, or even geographies, and often serve as conduits for faster, more efficient communication. They play a crucial role in learning, mentoring, problem-solving, and emotional support among employees.

Hidden Influence: The Power of Informal Relationships

While formal power comes from titles and positions, informal power arises from influence, trust, and access to information. Individuals who are central to informal networks—often referred to as "connectors," "brokers," or "hubs"—can significantly impact organizational outcomes, even if they hold no managerial authority.

These hidden influencers are often:

• The first to be consulted for advice or support
• Bridges between isolated teams or silos
• Catalysts of innovation and cultural change

Recognizing and leveraging informal power structures can dramatically improve leadership effectiveness, team dynamics, and overall organizational agility. This is where ONA becomes invaluable—it reveals the underlying social fabric that formal structures often overlook.

3. Key Components of ONA
Nodes and Ties

At its core, ONA relies on network theory, where the organization is modeled as a graph composed of nodes and ties.

• Nodes represent individuals, teams, or entities within the organization.
• Ties (also called links or edges) represent the relationships or interactions between nodes, such as communication, collaboration, or advice-seeking.

The strength, frequency, and direction of these ties can be quantified to better understand how information and influence flow across the organization.

Centrality Measures (Degree, Betweenness, Closeness)

Centrality measures help identify the most influential or strategically positioned individuals within a network:

• Degree Centrality refers to the number of direct connections a node has. A high degree centrality indicates someone well-connected and often influential.
• Betweenness Centrality captures how often a node appears on the shortest paths between other nodes. Individuals with high betweenness often act as bridges or brokers between otherwise disconnected groups.
• Closeness Centrality assesses how quickly a node can reach all other nodes in the network. Those with high closeness centrality are often efficient disseminators of information.

These metrics provide a deeper understanding of who drives communication, decision-making, and trust in an organization.

Network Density and Cohesion

• Network Density measures the proportion of actual connections to all possible connections within a network. A high-density network suggests strong cohesion, while a low-density network may indicate silos or fragmentation.
• Cohesion reflects how tightly-knit a group is. Cohesive networks are often more collaborative and resilient but may also suffer from groupthink or resistance to outside ideas.

Analyzing these factors helps assess the overall health and connectivity of organizational systems.

Subgroups and Clusters

Subgroups or clusters are smaller, tightly connected groups within the larger network. These can be:

• Functional clusters (e.g., teams working on the same project)
• Social clusters (e.g., friends who regularly interact)
• Knowledge clusters (e.g., experts in a specific field)

Understanding clusters is key to identifying knowledge hubs, innovation zones, or even silos that may hinder collaboration. ONA helps organizations navigate these micro-networks to optimize performance and integration.

3. Key Components of ONA (continued)
Network Density and Cohesion

Network density refers to the level of interconnectedness among nodes in a network. It is typically expressed as a ratio: the number of actual connections divided by the number of possible connections. A high-density network indicates that most members are well connected with each other, which can enhance communication, trust, and collaboration.

• High-density networks are often found in close-knit teams or long-standing departments. These networks foster loyalty and support but may become resistant to change or new perspectives.
• Low-density networks, by contrast, may suffer from communication gaps and siloed information but can also exhibit greater adaptability by integrating diverse viewpoints.

Cohesion, on the other hand, is the strength of the bonds that tie members of a group together. Cohesive groups exhibit strong mutual trust, frequent interactions, and high levels of interdependence. In ONA, measuring cohesion helps assess how robust and resilient a network is. Highly cohesive groups can be great incubators for innovation but must be carefully managed to avoid exclusivity or stagnation.

Subgroups and Clusters

In any network, subgroups or clusters emerge when certain individuals interact more frequently with each other than with those outside their group. These sub-networks often arise naturally based on common functions, roles, goals, or social affiliations.

Subgroups can serve both positive and negative roles:

• Positive effects include enhanced collaboration, knowledge specialization, and faster decision-making within the cluster.
• Negative effects may include siloed thinking, resistance to cross-functional efforts, and duplication of work.

ONA helps detect these clusters and determine whether they are functioning as productive knowledge hubs or isolated units that hinder enterprise-wide cohesion. Strategic interventions—like facilitating cross-cluster projects—can help organizations tap into the strengths of subgroups while mitigating risks.

4. Types of Organizational Networks

Organizational Network Analysis does not treat all networks equally. In fact, ONA can be applied to a variety of functional networks within an organization, each offering different insights. The main types include communication, collaboration, trust and advice, and innovation and knowledge-sharing networks.

Communication Networks

Communication networks map how information flows within an organization. These networks can include both formal (e.g., official memos, scheduled meetings) and informal (e.g., chats, hallway conversations) exchanges. They reveal the frequency, direction, and volume of communication between individuals or groups.

In analyzing communication networks, ONA identifies:

• Bottlenecks where communication gets delayed or filtered
• Overloaded individuals who may be overwhelmed with requests
• Isolated employees who may be out of the information loop

Optimizing communication networks can significantly improve organizational transparency, responsiveness, and employee engagement.

Collaboration Networks

Collaboration networks illustrate who works with whom to complete tasks, projects, or goals. They focus on the flow of work rather than just information. These networks can be dynamic, evolving as teams form and dissolve across projects.

ONA can use collaboration networks to assess:

• Project effectiveness and coordination
• Redundancies in efforts
• Opportunities to break silos between departments

High-performing collaboration networks often cut across hierarchical levels, departments, and even geographical boundaries—making them central to organizational agility.

Trust and Advice Networks

These networks reveal the flow of guidance, mentoring, and emotional support in an organization. Rather than focusing on who works together, trust and advice networks explore who people turn to when they need help, reassurance, or expertise.

These networks expose:

• Informal leaders or go-to experts who are key influencers
• Dependence chains that may create risk if one node leaves
• Underutilized talent whose expertise isn’t widely known

Understanding these networks is especially crucial in leadership development, succession planning, and creating a supportive culture. People rarely share confidential thoughts or ask for help based on hierarchy—they do it based on trust.

Innovation and Knowledge-Sharing Networks

Innovation networks chart how ideas, skills, and expertise spread across the organization. These networks are crucial for identifying how creativity, new thinking, and specialized knowledge are cultivated and disseminated.

In many organizations, innovation doesn’t come from a single department—it arises from the intersection of different teams and perspectives. ONA uncovers:

• Knowledge brokers who connect unrelated domains
• Isolated experts whose input could spark innovation if better connected
• Teams that generate ideas but lack access to the resources to implement them

Mapping innovation networks allows leaders to build better cross-functional ecosystems, create idea incubators, and cultivate a culture that values experimentation and learning.

5. The Process of Conducting ONA
Step-by-Step Methodology

Conducting Organizational Network Analysis (ONA) involves a structured process that blends qualitative insights with quantitative network data. The goal is to uncover the real dynamics behind how work gets done, where bottlenecks exist, and who holds influence in an organization. A step-by-step methodology generally includes the following stages:

1. Define Objectives
   Clearly identify why you are conducting ONA. Objectives may include improving collaboration, facilitating change management, identifying key influencers, or assessing team effectiveness.
2. Select the Network Type and Scope
   Decide whether the analysis will focus on communication, collaboration, trust, or innovation networks. Also, determine the boundaries—will it include the entire organization, a specific department, or a project team?
3. Identify Participants and Nodes
   Choose the individuals or groups who will be represented as nodes. Ensure that selection aligns with the scope and purpose of the analysis.
4. Design Data Collection Strategy
   Determine which data sources and collection methods (surveys, logs, interviews) will best capture relationships between the selected nodes.
5. Collect and Validate Data
   Gather data and ensure its accuracy and completeness. Cross-validate with organizational leaders and participants if necessary.
6. Visualize the Network
   Use visualization tools to create network maps. These graphs help identify patterns, clusters, gaps, and outliers.
7. Analyze Metrics and Patterns
   Apply network analysis measures such as centrality, density, and cohesion to draw meaningful conclusions.
8. Report Findings and Recommend Actions
   Present the results in a digestible format and suggest practical interventions based on insights.
9. Monitor and Reassess
   Consider repeating ONA periodically to track changes and improvements over time.
   
   Data Collection Methods (Surveys, Email Logs, Observations)

ONA relies on data that reflects real interactions. The most common collection methods include:

• Surveys
  Structured questionnaires are used to ask participants whom they interact with, seek advice from, or collaborate with. Surveys can be customized depending on the network type.
• Email and Communication Logs
  Digital trace data, like email metadata (not content), chat logs, or collaboration tools, provides objective and high-frequency information on communication flows.
• Observations and Interviews
  Qualitative methods, such as ethnographic observation or semi-structured interviews, enrich ONA by offering context to raw data. They help explain why certain patterns exist.

Each method has trade-offs in terms of reliability, completeness, and ethical sensitivity, so a combination is often most effective.

Visualization and Analysis Tools

Specialized software is used to create network graphs and calculate metrics. Popular tools include:

• Gephi – Open-source and powerful for complex visualizations.
• NodeXL – An Excel-based tool ideal for beginners and small networks.
• Pajek – Best suited for large networks and academic research.
• Kumu – A web-based tool known for storytelling and stakeholder mapping.
• R and Python (with packages like igraph or NetworkX) – For advanced users looking to customize analysis with statistical depth.

Visualization enables stakeholders to intuitively grasp where influence resides, how communication flows, and where interventions are needed.

Ethical Considerations and Privacy

ONA involves sensitive data about people’s relationships, influence, and communication behavior. This raises serious ethical and privacy concerns, including:

• Informed Consent: Participants must understand how their data will be used and agree to participate.
• Anonymity and Confidentiality: Sensitive findings should be anonymized, and individual identities protected.
• Transparency: Stakeholders should be informed about the purpose, methods, and outcomes of the ONA.
• Data Security: Robust measures should be taken to protect data from breaches or misuse.

Ethics must be embedded at every step—not only to protect participants but also to ensure trust and credibility in the analysis.

6. Mapping Informal Power and Influence
Identifying Key Influencers and Connectors

One of the most valuable applications of ONA is its ability to spotlight individuals who wield significant informal power in an organization. These individuals may not hold senior titles but are central to communication, collaboration, and trust networks.

• Influencers are people whom others go to for advice, information, or emotional support. Their positions in the network—often with high degree or betweenness centrality—make them vital to organizational function.
• Connectors bridge different parts of the network, facilitating cross-functional or cross-geographical collaboration. They reduce fragmentation and foster innovation.

Identifying these key figures allows organizations to:

• Leverage their influence during change initiatives
• Involve them in decision-making or mentoring
• Protect knowledge continuity by preparing for succession
  
  Role of Gatekeepers, Brokers, and Boundary Spanners

In any organizational network, certain individuals play strategic roles that make them critical to the organization’s social infrastructure:

• Gatekeepers control the flow of information between different parts of the organization. They often act as filters or translators of information.
• Brokers connect otherwise unconnected individuals or teams. They are essential in fostering innovation, spreading best practices, and reducing redundancy.
• Boundary Spanners link internal networks with external stakeholders, partners, or customers. Their role is particularly important in open innovation, market intelligence, and ecosystem collaboration.

These roles, although informal, are often more impactful than formal job descriptions. By visualizing where these people sit in the network, leaders can make more informed decisions about whom to involve in critical initiatives.

Influence Beyond Hierarchies

Traditional hierarchical models assume that influence flows from the top down. However, ONA often reveals that power and influence are distributed more organically.

Examples of influence beyond hierarchy include:

• A mid-level engineer who is the go-to person for solving technical problems
• An admin assistant who knows the schedules, moods, and preferences of key executives
• A junior analyst who connects disparate project teams through informal chats and Slack channels

Recognizing this informal influence reshapes leadership models. Modern organizations increasingly rely on network-based leadership, where authority is derived from influence, trust, and credibility rather than title or tenure. ONA empowers such a paradigm shift by providing visibility into the invisible currents of power.

7. Applications and Use Cases of ONA

Organizational Network Analysis has evolved from a theoretical research tool into a strategic instrument with a wide range of real-world applications. Whether used to enhance day-to-day operations or support large-scale transformations, ONA provides actionable insights that traditional organizational charts and performance data cannot.

Enhancing Collaboration and Communication

Effective communication is the backbone of any high-performing organization. ONA helps uncover how people actually interact—beyond formal structures—by mapping communication flows.

• It identifies communication bottlenecks where information is delayed or lost.
• Highlights isolated individuals or teams that may be missing critical updates.
• Reveals overburdened employees who may be acting as unintended hubs of communication.

Armed with these insights, leaders can reconfigure communication pathways, ensure more equitable distribution of information, and introduce tools or practices to foster healthy collaboration.

Change Management and Culture Transformation

Change initiatives often fail not because of poor strategy, but because of poor adoption. ONA can dramatically increase the chances of success by identifying informal influencers—those individuals who can promote, resist, or shape the adoption of change.

• Influencers can be enlisted to champion change and model desired behaviors.
• Resistant clusters can be identified early and engaged more sensitively.
• Cultural hotspots—areas of strong informal norms—can either help embed new values or act as barriers to transformation.

Thus, ONA becomes a powerful ally in aligning behavior and mindsets with strategic direction.

Talent Identification and Leadership Development

Traditional talent reviews often overlook individuals with high informal influence who don’t have high formal visibility. ONA corrects this blind spot by identifying:

• Unsung heroes who are critical to team function and morale.
• Potential future leaders who already act as information brokers or mentors.
• Employees who may be disengaged or underutilized, despite their network centrality.

This insight enriches talent development programs and succession planning efforts by incorporating actual behavior and impact, not just assessments or manager feedback.

Mergers, Acquisitions, and Restructuring

Mergers and acquisitions (M&A) bring together different organizational cultures, systems, and networks. Formal integration plans often overlook how work and influence actually flow within each company. ONA can:

• Map informal networks within both organizations before the merger.
• Identify connectors and cultural ambassadors who can help bridge divides.
• Highlight teams or individuals vulnerable to disengagement post-merger.

Similarly, in restructuring or downsizing, ONA helps ensure that essential connectors and knowledge holders are not inadvertently lost, preserving organizational memory and cohesion.

Crisis and Risk Management

In moments of crisis—such as leadership vacuums, compliance breaches, or sudden change—informal networks often play a decisive role. ONA enables organizations to:

• Activate key influencers who can calm, guide, or align employees.
• Map risk-prone nodes that are central but overloaded or isolated.
• Strengthen connections across weak or vulnerable parts of the organization.

Organizations that understand and manage their informal networks are better positioned to respond swiftly and cohesively under pressure.

8. ONA in HR and Leadership Strategy

As the workplace becomes more complex, dynamic, and human-centric, the role of Human Resources is evolving beyond transactional support into strategic enablement. ONA aligns perfectly with this evolution by offering data-driven insights into human behavior, connection, and performance.

Informing Succession Planning

Succession plans often rely on formal roles, tenure, and performance metrics. Yet, when a key leader leaves, what’s often missed is the informal influence that person held. ONA identifies:

• Employees who are central to decision-making and knowledge sharing.
• Hidden dependencies that may not be visible in organizational charts.
• Risk of disruption if certain individuals leave without a succession strategy.

With ONA, HR leaders can create robust and realistic succession plans that go beyond titles to include network-based influence and impact.

Supporting Diversity and Inclusion

Even in diverse organizations, networks can become insular, unintentionally excluding minority or marginalized groups from influential circles. ONA helps:

• Assess whether diverse employees are well integrated into key networks.
• Identify cultural silos or echo chambers that perpetuate exclusion.
• Spotlight champions and allies who can serve as bridges and mentors.

By making invisible barriers visible, ONA empowers D&I strategies with real-world, behavior-based evidence—transforming inclusivity from aspiration into action.

Managing Remote and Hybrid Teams

As remote and hybrid work environments grow, traditional visibility into team dynamics diminishes. Leaders may struggle to assess who is thriving, who is isolated, and how work actually flows. ONA provides clarity by:

• Mapping how virtual collaboration happens across time zones and platforms.
• Identifying employees who are becoming disconnected or underutilized.
• Ensuring that informal knowledge transfer is not lost due to physical distance.

This insight helps HR teams proactively manage engagement, prevent burnout, and maintain strong culture in distributed work environments.

Shaping Organizational Agility

In a rapidly changing world, agility is no longer optional—it is essential. Agile organizations need fluid communication, decentralized decision-making, and cross-functional collaboration. ONA accelerates this transition by:

• Diagnosing current state networks: Are they hierarchical or adaptive?
• Spotting nodes of resistance to agile practices.
• Promoting bridge-builders who connect different departments, functions, or geographies.

With this foundation, leaders can design interventions that move the organization closer to true agility—one built on responsive, trusted, and connected human networks.

9. Tools and Technologies Used in ONA

As ONA evolves into a practical tool for decision-making, various technologies have emerged to support its deployment at scale. These tools enable not just the visualization of networks, but also the integration of ONA with business systems, making the insights directly actionable.

Software Platforms (e.g., Polinode, Kumu, OrgMapper)

Several specialized software platforms are designed to conduct ONA with high levels of precision and usability:

• Polinode: A robust platform that allows for dynamic network surveys, visualizations, and advanced analytics. It is widely used in corporate settings for mapping influence and information flows.
• Kumu: Known for its flexible and visually appealing maps, Kumu is especially useful for storytelling and presenting complex systems in accessible ways.
• OrgMapper: Developed by Maven7, OrgMapper offers various modules for change management, influencer identification, and post-merger integration, tailored to large enterprises.

These platforms typically allow users to import data, run centrality and cohesion analyses, and visualize networks through interactive dashboards.

Data Integration with HRIS and Communication Systems

To scale ONA effectively, it’s crucial to integrate it with existing organizational systems:

• HRIS (Human Resource Information Systems): Integration allows for the layering of network data with formal HR metrics such as performance scores, tenure, or role history.
• Communication Platforms: ONA tools can analyze metadata (not content) from platforms like Slack, Microsoft Teams, Outlook, and Zoom to map out actual interaction patterns.

This enables organizations to conduct passive ONA—gathering real-time or longitudinal network data without deploying disruptive surveys.

AI and Machine Learning in Network Pattern Detection

Artificial Intelligence and machine learning are becoming increasingly essential in large-scale ONA:

• Pattern Recognition: ML models can detect anomalies or recurring motifs in networks, such as signs of burnout or disconnection.
• Predictive Modeling: AI can forecast network evolution under different conditions—such as leadership change or team restructuring.
• Clustering and Community Detection: Unsupervised learning methods like k-means or modularity optimization help discover hidden subgroups or silos.

These technologies not only automate analysis but also enhance the depth of insights, making ONA more proactive than reactive.

10. Challenges and Limitations of ONA

Despite its benefits, Organizational Network Analysis is not without limitations. Understanding these challenges is critical for responsible and effective use.

Data Accuracy and Interpretation

• Incomplete Data: Self-reported surveys may suffer from recall bias or non-responses. Passive data may omit informal, face-to-face interactions.
• Misinterpretation: Centrality does not always mean influence; ties can be positive (trust, advice) or negative (conflict, overload).
• Temporal Sensitivity: Networks evolve rapidly, and snapshots may miss critical fluctuations.

Hence, careful triangulation with other data sources and contextual understanding is necessary.

Employee Concerns and Resistance

• Perception of Surveillance: Employees may fear that ONA tools are invasive, especially if used without transparency.
• Change Fatigue: Involving employees in multiple surveys or network assessments can lead to disengagement.
• Trust and Consent: Without clear communication, even ethical ONA practices may be viewed with suspicion.

Building trust and involving employees early in the process are key to overcoming resistance.

Ethical and Legal Constraints

• Privacy Regulations: ONA must comply with laws like GDPR, especially when analyzing communication metadata.
• Anonymity and Consent: Ethical use requires informed consent and safeguards to prevent misuse of data (e.g., targeting individuals based on network position).
• Bias and Discrimination Risks: Algorithms used in ONA may unintentionally reinforce biases if not properly designed and audited.

Organizations must establish clear governance frameworks to ensure that ONA serves employee well-being as well as business goals.

Scalability and Complexity in Large Organizations

• Computational Load: Large, dense networks may require significant processing power and storage.
• Visualization Challenges: Complex networks are hard to interpret visually, especially for non-technical audiences.
• Actionability: Insights from large networks may overwhelm decision-makers if not properly filtered or contextualized.

Scalability demands both technical sophistication and effective stakeholder communication strategies.

11. Future Trends in Organizational Network Analysis

The future of ONA lies at the intersection of real-time analytics, predictive intelligence, and broader integration with strategic people management frameworks.

Predictive ONA

Predictive ONA aims to anticipate future network states and behaviors. For example:

• Predicting team performance or burnout risk based on changes in interaction patterns.
• Anticipating turnover by detecting disconnection from core networks.
• Modeling the impact of proposed structural changes on informal collaboration.

These forecasts enable leaders to intervene proactively rather than reactively.

Real-Time Network Monitoring

With the rise of digital collaboration platforms, it's now possible to monitor networks in near real-time:

• Dashboards can track evolving connections, information flow, and engagement levels.
• Alerts can be triggered when certain thresholds are met (e.g., drop in connectivity, overload of key hubs).
• Continuous feedback loops allow for agile organizational design.

Real-time ONA empowers dynamic decision-making and more responsive leadership.

Integrating ONA with People Analytics and Digital Twins

ONA is increasingly being integrated into broader People Analytics ecosystems:

• People Analytics: Combining ONA with engagement, performance, and sentiment data provides a multidimensional view of workforce health.
• Digital Twins of Organizations (DTOs): A DTO is a virtual replica of an organization’s structure and behavior. ONA feeds into DTOs by representing the informal dimension of work relationships, enabling simulations and what-if analyses.

These integrations position ONA as a core element of future-ready HR and organizational strategy, moving from a diagnostic tool to a strategic cockpit for transformation.

12. Case Studies and Real-World Examples

Real-world applications of Organizational Network Analysis (ONA) provide compelling evidence of its strategic value. From improving innovation to managing post-merger transitions, these case studies reveal how ONA transforms insights into impactful decisions.

ONA in a Global Tech Company

Background:
A multinational technology firm faced a challenge with cross-functional collaboration. Despite a formally flat structure, product delays and siloed thinking persisted across engineering, design, and marketing teams.

Implementation:
ONA was conducted using metadata from internal messaging platforms and structured surveys. The goal was to visualize how information actually flowed across departments and who the informal influencers were.

Findings:
The analysis revealed that certain mid-level engineers acted as key connectors, bridging product and design teams. However, they were not formally acknowledged or empowered in the decision-making hierarchy.

Outcome:
The company restructured team workflows to formally recognize and support these connectors. By including them in early-stage planning and leadership development programs, time-to-market improved by 22% and inter-team conflicts reduced significantly.

Takeaway:
ONA uncovered hidden influencers and reshaped collaboration pathways, leading to measurable improvements in product delivery and team alignment.

Improving Innovation in a Healthcare Organization

Background:
A healthcare organization with multiple hospitals and research centers aimed to boost innovation by fostering better knowledge-sharing across locations.

Implementation:
ONA was applied to map trust and advice networks among physicians, researchers, and administrators. The analysis included both survey-based and passive data collection.

Findings:
The network maps showed that while formal teams were well-structured, the actual advice networks were localized, with limited cross-site interaction. Senior researchers often served as knowledge hubs, but newer employees were disconnected.

Outcome:
The leadership used these insights to establish cross-site innovation teams and mentorship programs. Additionally, regular “Innovation Cafés” were introduced to encourage informal exchange.

Result:
Within 12 months, the number of cross-functional projects doubled. Employee engagement scores in R&D also rose by 18%.

Takeaway:
ONA was instrumental in identifying silos and designing interventions that sparked cross-boundary collaboration and innovation.

Cultural Integration Post-Merger Using ONA

Background:
Following a merger between two financial service firms, leadership struggled with integrating different organizational cultures and ensuring alignment.

Implementation:
ONA was conducted to map existing informal relationships across the two entities, identify gatekeepers, and understand collaboration bottlenecks.

Findings:
The analysis showed that employees continued to operate within their pre-merger clusters. Only a handful of individuals had ties across both organizations, acting as critical brokers for knowledge flow.

Outcome:
These cross-company brokers were given facilitation roles in culture-building workshops and onboarding efforts. Joint task forces were created around them to promote integration.

Result:
Six months later, network cohesion scores improved by 40%, and early attrition among merged employees dropped significantly.

Takeaway:
ONA enabled the company to diagnose and accelerate cultural integration by activating internal brokers and reducing resistance to change.

13. Conclusion
Key Takeaways

Organizational Network Analysis (ONA) is more than a visualization tool—it’s a strategic framework for decoding how work truly gets done. It reveals the underlying social fabric of organizations, highlighting informal relationships that are often more influential than formal hierarchies.

Key concepts like centrality, network density, subgroups, and gatekeepers help decision-makers understand who influences what, where bottlenecks exist, and how ideas propagate. From mapping innovation pathways to identifying hidden talent and enabling smoother change management, ONA has widespread applications.

Strategic Value of ONA in the Modern Workplace

In today’s rapidly evolving workplace, where teams are remote, hybrid, or distributed, informal networks shape everything—from communication flow to employee engagement. ONA provides:

• A diagnostic lens for identifying strengths and vulnerabilities in collaboration.
• A development tool for leadership pipelines and succession planning.
• A predictive model for managing change, mitigating risk, and enhancing agility.

Moreover, the integration of ONA with HR analytics, AI, and digital twins will only deepen its impact, turning it from a diagnostic practice into a real-time strategic compass.

Final Thoughts on Mapping Influence and Informal Power

Influence does not reside solely in job titles or organizational charts—it lives in conversations, trust, mentorship, and shared purpose. ONA helps leaders see the invisible, value the informal, and activate the influential. In doing so, organizations become not only more connected but also more resilient, innovative, and human-centered.

Frequently Asked Questions (FAQs)

1. What is Organizational Network Analysis (ONA)?
Organizational Network Analysis (ONA) is a method used to study patterns of interaction, communication, collaboration, and influence within an organization by mapping relationships between individuals, teams, or departments.

2. How does ONA differ from traditional organizational charts?
Traditional charts depict formal hierarchies, while ONA visualizes informal relationships and real communication flows, highlighting hidden influencers, connectors, and information bottlenecks.

3. Why is ONA important in modern workplaces?
ONA reveals how work truly gets done, enabling better decision-making in areas like collaboration, change management, innovation, and leadership development, especially in remote or hybrid work settings.

4. What are the key components of an organizational network?
Networks consist of nodes (people) and ties (relationships). Core metrics include centrality (degree, betweenness, closeness), density, cohesion, subgroups, and brokers.

5. What types of networks can be analyzed in ONA?
Common types include communication networks, collaboration networks, trust/advice networks, and knowledge-sharing or innovation networks.

6. How is ONA data collected?
Data is gathered using surveys, email metadata, meeting logs, collaboration tools, observation, and integration with communication platforms like Slack or Microsoft Teams.

7. Is employee consent required for ONA?
Yes. Ethical ONA practices involve transparency, consent, and data anonymization to respect employee privacy and comply with legal standards.

8. Can ONA help identify future leaders?
Absolutely. ONA can uncover informal influencers who demonstrate leadership qualities, making it valuable for succession planning and talent development.

9. How often should organizations conduct ONA?
It depends on organizational goals. Some conduct it annually for strategic planning, while others perform real-time or quarterly ONA to monitor ongoing changes and dynamics.

10. What software tools are used for ONA?
Popular tools include Polinode, Kumu, OrgMapper, and NodeXL. Some HR platforms also integrate ONA capabilities through analytics dashboards.

11. What are the limitations of ONA?
Challenges include data accuracy, interpretation biases, resistance from employees, scalability issues, and ethical concerns over privacy.

12. How can ONA be applied during mergers or restructuring?
ONA can assess integration levels, identify key brokers between merging entities, and facilitate smoother transitions by strengthening cross-group relationships.

13. What is the role of AI in modern ONA?
AI enhances ONA by identifying patterns, predicting influence or burnout risks, and enabling real-time insights through network monitoring and automation.

14. Can ONA support diversity and inclusion initiatives?
Yes. It helps uncover structural biases in networks, reveals exclusion patterns, and supports more inclusive leadership and team-building efforts.

15. Is ONA relevant for small businesses?
Definitely. Even in small teams, informal dynamics matter. ONA helps leaders understand who drives collaboration and influence, improving team performance and morale.