Mark Outwaite explores the common misconceptions surrounding Organisational Network Analysis (ONA), a powerful tool that reveals how collaboration truly happens beyond formal structures. Despite its potential, ONA is often misunderstood or misused by leaders across sectors, from healthcare to global corporations, due to enduring myths that obscure its real value.

In my Farewell NHS England blog in March, I explained why we need to recognise and mitigate the impact of NHS reorganisaton on organisational and system networks, if real improvement is to be realised. To be able to do this, we need Organisational Network Analysis (ONA): the study of the informal relationships and information flows within an organisation. ONA provides an “X-ray” of how people actually collaborate, beyond the lines and boxes of formal org charts. Yet across industries – from hospitals and public agencies to multinational corporations – several persistent myths cause senior leaders and change agents to misjudge ONA’s value or misapply its findings.

Below, I debunk the most common misconceptions about ONA, focusing on strategic and implementation challenges and offer evidence-based practices to counter each myth. 

Misconception 1:  “We already know how our organisation’s networks work.” 

Leaders often assume the formal hierarchy, or their own experience reveals how work gets done. In reality, informal networks can look very different.  For example, an ONA at a large firm found a mid-level manager was the only bridge connecting a technical division to the rest of the company, while a senior vice-president was isolated at the network’s edge.  

None of these insights was visible from the official org chart. Relying on hierarchy and gut feel alone can blind executives to who the real influencers and information brokers are in day-to-day operations. 

  • Reality: Research shows that people with formal authority or big titles aren’t necessarily the ones driving collaboration on the ground. In one study, not a single executive could correctly name their organisation’s top informal influencers before conducting an ONA – a clear sign that intuition and org charts often miss critical connectors. As Rob Cross observes, ONA often reveals patterns of collaboration “entirely different” from what formal management layers perceive. In short, informal networks do not simply mirror formal structures and leaders typically do not already know all the key relationships.
  • Best Practice: Validate assumptions with data. Rather than assuming you know who talks to whom, use ONA to map the actual network of interactions. Even a small pilot ONA can uncover hidden hubs, bridges and silos, giving leaders a more accurate picture. Senior leaders in both the public and private sectors have found value in “letting the data speak” – identifying previously overlooked influencers and critical communication channels – and then incorporating those insights into their change programmes. By supplementing managerial intuition with hard network evidence, you ensure your transformation efforts engage the real opinion leaders and troubleshoot the actual bottlenecks in your organisation. Leaders should treat the org chart as a starting hypothesis, not the full story and remain open to ONA findings that challenge their assumptions. 

Misconception 2:  “ONA is just an HR analytics fad, not a strategic tool.” 

Some executives see ONA as a trendy HR experiment – nice in theory, but not essential for “serious” business decisions. In truth, ONA is increasingly used as a strategic decision-making tool. It is not confined to HR; it spans multiple business domains and sectors. Forward-thinking organisations deploy ONA to inform mergers and acquisitions, drive innovation, improve patient care coordination and accelerate change management. Far from a passing fad, network analysis aligns directly with strategic needs in today’s interconnected work environment. 

  • Reality: Many leading companies (including global banks, tech firms and manufacturers) are already using ONA at scale. Its applications go well beyond HR metrics. For example, organisations use ONA during restructures and mergers to mitigate the risks of losing key brokering and knowledge roles or identifying integration pain points and to decide how best to realign teams. It’s also applied in workforce planning and innovation initiatives to pinpoint where collaboration is thriving or stuck. Crucially, ONA helps leaders see where value is created in the network, not just on paper. Some companies have even reported faster project delivery times and higher profits by acting on network insights. These are tangible business outcomes, not HR vanity projects. 
  • Best Practice: Make ONA a leadership priority tied to business goals. Treat network analysis as a strategic tool – akin to market analysis or financial modelling – that informs core decisions. Secure an executive sponsor (for example, a COO or transformation lead) who views ONA insights as integral to achieving objectives like breaking down silos, improving innovation or speeding up cross-team workflows. By explicitly linking ONA findings to key performance indicators (e.g. time-to-market, quality improvements, staff retention), you elevate it from a “nice-to-have” to a must-have tool for organisational success. This cross-functional mindset ensures ONA isn’t siloed in HR: in practice, departments such as operations, strategy and even healthcare administration can all leverage network data to guide their interventions. 

Misconception 3: “ONA produces interesting graphs but no actionables.” 

There is a myth that ONA results in pretty network maps and academic insights, but little practical value – that it tells you what is happening (who connects to whom) but not what to do about it. This misconception arises when ONA is done in isolation or without a clear purpose. In reality, when tied to specific questions and a collaborative approach to sense-making, ONA yields highly actionable intelligence. It can spotlight concrete problems (like an overburdened manager or an isolated team) and point to solutions (redistribute workload, connect the silo to the rest of the organisation, etc.). 

  • Reality: A well-scoped ONA combined with co-design and collaborative sense-making directly drives action. Organisations have used network insights to reduce employee turnover by ensuring those at risk have stronger support networks and to promote overlooked talent who were influential but hidden in the hierarchy. ONA can flag individuals at risk of burnout due to collaboration overload, prompting managers to redistribute tasks before people quit. It also reveals inclusion gaps, identifying employees who are isolated due to unconscious bias, which leaders can then address with targeted inclusion efforts. These outcomes – lower attrition, higher productivity, more equitable teams – demonstrate clear business impact. In one example, understanding informal networks allowed a company to cut project completion times and boost performance metrics by streamlining information flow. The insights aren’t merely academic; they translate into measurable improvements when acted upon. 
  • Best Practice: Define the questions and follow through. To counter the “no action” myth, begin any ONA with specific strategic questions (e.g. “Why is our innovation stalling in Region X?” or “Who are the key connectors for our digital transformation?”). This focus ensures the data collected points to decisions. After mapping the network, integrate the findings into your action plans: for instance, if ONA uncovers a critical expert who is under-utilised at the periphery, deliberately involve that person in relevant projects or decision loops. If it shows a team is isolated, create cross-functional task forces or informal meet-ups to bridge the gap. It’s also wise to combine ONA with other data (like performance or engagement metrics) to validate insights and craft interventions. Ultimately, treat the network map not as an end product but as a diagnostic tool – one that comes with a to-do list. Many organisations establish ongoing review processes (e.g. quarterly network health checks) to ensure ONA insights lead to concrete actions and track the results (such as improved collaboration scores or faster problem resolution). This closes the loop from analysis to execution, disproving the notion that ONA is just “interesting” but ineffectual. 

Misconception 4: “Mapping networks is intrusive – it’s ‘Big Brother’ watching.” 

A common implementation concern is that ONA equates to spying on employees. Senior leaders and staff alike may worry that analysing who communicates with whom will breach privacy, expose personal secrets, or erode trust. This fear can be especially pronounced in sectors like healthcare or government, where confidentiality is paramount, but it exists in corporate settings too. However, this is a misconception – ONA can be conducted in a privacy-conscious, ethical way and when done transparently it is seen as a positive initiative rather than surveillance. 

  • Reality: Privacy concerns are valid but manageable. ONA  takes two forms – passive, which involves analysing existing flows such as email or messaging services, and active, which is survey based. In both cases it is possible to design in assurances about how the data will be used.  For instance, passive ONA analyses use aggregated, metadata-level information not the content of personal messages. Active ONA surveys often restrict access to the raw information unless a participant gives their agreement to it being disclosed. The goal is understanding network structure – e.g. who collaborates frequently – not reading anyone’s emails or private chats. Recognising these worries, organisations implementing ONA typically spend considerable effort engaging staff in understanding the purpose, co-design of the process and close involvement in sense-making of the outputs. Concerns can be allayed by clarifying that ONA is focused on work-related connection patterns. Importantly, ethical ONA initiatives do not judge individuals for their network position; instead, they aim to support people (for example, by helping overburdened staff or ensuring no one is left isolated). In some projects individual identities in the analysis are protected until such time as those individuals agree otherwise. Often where existing networks are properly engaged and take ownership of their own ‘network health check’ they are keen to ensure full transparency to get the most out of the exercise. Leading companies acknowledge that while they have a legitimate interest in understanding how work gets done, they must balance it with respect for employee privacy. 
  • Best Practice: Prioritise transparency and employee consent. To counter the “Big Brother” myth, openly communicate why the organisation is doing ONA, what data will be collected and how insights will be used. Frame it as a way to improve the work experience (e.g. “to identify where people might need more support or recognition”), not as employee monitoring. Many organisations succeed by making ONA opt-in or at least informing employees in advance and giving them a say. Where there is sensitivity – for example in challenging workplace relationship contexts data anonymisation and aggregation are key tools – share only broad network trends or anonymised maps with managers, unless individuals have agreed to be identified. Additionally, involve an ethics or data privacy officer to review the process, which builds trust that the analysis is above-board. In practice, when employees see that ONA results lead to positive changes – such as more manageable workloads or better team connectivity – their fears subside. The process can even increase trust if handled correctly: it signals that leadership cares about the quality of collaboration and is willing to invest in understanding and improving it. In summary, an open, ethical approach will dispel the misconception that ONA is “spying” and instead highlight it as a tool for mutual benefit. 

Misconception 5: “The more connections, the better – we just need people to collaborate more.” 

At first glance, a dense, highly connected network might seem ideal. Senior leaders sometimes assume that maximising communication (more meetings, cc’ing more people on emails, breaking all silos) will automatically improve performance. This is a myth. In practice, quality and structure of connections matter far more than sheer quantity. Overloading people with interactions can create bottlenecks and burnout, while a smartly targeted network yields better results than an over-connected one. 

  • Reality: Collaboration overload is a real risk. ONA studies frequently find that a small fraction of employees shoulders a disproportionate share of information flow. For example, research by Rob Cross shows roughly 3–5% of people account for 20–35% of value-adding collaborations. These individuals become bottlenecks if everyone is routed through them, leading to delays and stress – an overloaded connector can slow decision-making or burn out from the burden. Indeed, ONA data often identify key players who are “too connected”: they attend every meeting, field every question and as a result, they and their teams suffer from fatigue. Simply increasing the number of interactions or aiming for an all-to-all network can backfire. Moreover, not all connections are equal: a few high-quality, trusting relationships can be far more productive than dozens of superficial contacts. An overly dense network can also create noise, where employees are distracted by excessive communications that don’t concern them. Thus, effective networks strike a balance – ensuring critical links exist without inundating everyone with endless collaboration. 
  • Best Practice: Focus on quality, roles and load-balancing in networks. Rather than exhorting everyone to “collaborate more,” use ONA to pinpoint where better collaboration is needed and where there may be diminishing returns. For instance, if ONA reveals one manager is a single point of contact for five teams, consider redistributing responsibilities or appointing deputies to share the load. Encourage targeted connection-building: connect otherwise isolated groups or individuals (bridging a known silo to the rest of the organisation), but also streamline excessive linkages (for example, freeing up an over-taxed expert by routing certain queries elsewhere). It’s useful to monitor network health metrics such as network density and centrality – not to maximize them blindly, but to keep them in an optimal range (neither too sparse nor too clogged). Educate leaders that more is not always better: the aim is effective collaboration. This might mean setting norms like “fewer, more focused meetings” or using smaller working groups, so that connectivity serves a purpose. By using ONA to guide these interventions, organisations can ensure they strengthen the right connections (to fill gaps) while lightening the load on bottlenecks, leading to a healthier, more sustainable network. 

Misconception 6: “ONA is too complicated and resource-intensive to implement successfully.” 

The final common myth is a practical one: the belief that ONA is prohibitively difficult – requiring big budgets, complex software, data scientists, or disruptive data collection – especially in non-corporate settings or smaller organisations. This misconception can deter leaders from even attempting network analysis. In reality, ONA is quite feasible with today’s tools and best practices. While it does require planning and care (like any analytic project), it need not be an IT nightmare or a massive expense. 

  • Reality: It’s true that poor implementation can pose challenges. ONA relies on quality data – incomplete or inaccurate data will yield flawed insights. Integrating data from various sources (email, surveys, org charts) can require effort and some technical setup is needed to analyse and visualise the networks. However, the field has evolved significantly: there are now user-friendly ONA platforms and expert consultancies that handle much of the heavy lifting. Many organisations start with simple survey-based ONA, which asks employees a short series of questions about their work connections. In fact, effective ONA surveys often need only on the order of 10 questions to map key relationships. What’s more important than technical complexity is obtaining a high participation rate – ideally around 80% or more – so the network picture is complete. With clear communication and leadership support, such response rates are achievable. Even when using passive data (like communication metadata), pilot projects can be done with manageable scope (e.g. one division or a specific process) to prove the concept before scaling up. In short, ONA implementation is scalable: it can start small and grow, rather than requiring an all-or-nothing investment upfront. Organisations ranging from resource-strapped public health departments to large multinationals have successfully implemented ONA by starting with focused objectives and leveraging available tools. 
  • Best Practice: Start small and build capability. Demystify ONA by launching a pilot in a controlled environment – for example, map the network within a single department or around a single business process. This allows you to work out data collection and privacy kinks on a smaller scale. Use specialised ONA software or services that fit your needs; many platforms integrate with common systems (email, MS Teams, etc.) or provide simple survey modules, so you don’t have to develop methodology from scratch. Ensuring executive sponsorship is critical: a senior champion can secure resources and signal that this is a priority, not a side project. Also, invest in explaining the value to participants (what’s in it for them), which boosts engagement and data quality. Once the pilot yields insights, publicise a couple of quick wins (e.g. “ONA helped us cut duplicate meetings by 30% in Department X”) to build momentum. From there, you can expand ONA to other parts of the organisation or make it an ongoing practice. Another tip is to partner with experts – many consultancies and academic groups offer guidance on ONA and can help train your internal team, easing the learning curve. By taking a phased and supported approach, even organisations without big analytics teams can harness ONA effectively. Over time, you can grow your internal capability to conduct network analyses regularly, embedding it into your decision-making without an excessive burden. The key is to recognise that ONA is a manageable project – one that pays dividends by illuminating solutions to complex organisational challenges. 

Conclusion 

Organisational Network Analysis offers a powerful lens on how work truly gets done, but myths and misconceptions can hinder its adoption and impact. Senior leaders and change agents in any sector should recognise that informal networks hold critical insights – insights that often defy conventional wisdom but are essential for successful change. By dispelling the myths (from “we already know this” to “it’s too hard to do”) and embracing evidence-based practices, organisations can unlock ONA’s full value. Whether in healthcare, the public sector or corporate world, the lesson is the same: understand your networks and you can lead more effectively. ONA, approached with the right mindset and methods, becomes not just a diagnostic tool but a strategic asset – guiding more informed, inclusive and agile leadership decisions in today’s connected age. 

  • Read my guide to discover and make the most of the connections in your organisations 
  • Join my interactive webinar with Tracey Watson and Victoria Betton on 1st July to as we discuss the key steps to Networks Insight, how it can be used, and the impact it can have – with real use cases.

Sources: 

  • Cross, Rob et al., “Six Myths About Informal Networks — and How To Overcome Them,” MIT Sloan Management Review (2002). 
  • TechTarget, “What Is Organizational Network Analysis (ONA)?” (July 2024), definition and applications . 
  • MyHRFuture (D. Green), “The Role of Organisational Network Analysis in People Analytics,” (Nov 2022), on ONA benefits and examples . 
  • Innovisor (J. Hansgaard), “Five Misconceptions About Internal Influencers,” (Feb 2023), on hidden influencers and their surprising traits . 
  • Performica, “Don’t be afraid of ONA – it could be the key to a happier workplace,” (Aug 2023), on overcoming privacy fears and identifying key collaborators . 
  • Goldminz, Itamar, “Single-Player Mode: Unblocking ONA Adoption,” OrgHacking (Nov 2024), on privacy concerns and the need for transparency . 
  • Entromy, “The Complete ONA Playbook for Senior Leaders,” (2021), on implementation best practices (survey design, response rates, sponsorship) .