Organizational network analysis (ONA) measures and graphs patterns of collaboration by examining the strength, frequency and nature of interactions between people in networks.
ONA provides detailed information about hidden factors for success, such as flow of information, decision-making, revenue producing collaborations, innovation, inclusion—even trust, purpose and energy.
Organizational Networks Are Hidden Sources of Strategic Success
Often, network analysis reveals patterns of collaboration and influence that are very different from the formal hierarchical structures that leaders rely upon to understand operations and make decisions.
Consider this simplified comparison of the formal org structure and the informal network, drawn from a much larger ONA in the exploration and production division of a major petroleum organization. Names and identifying details have been changed for confidentiality.
This ONA identifies mid-level managers who are critical to information flow. Note the very central role of Mitchell; he is also the only point of contact between members of the production division and the rest of the network.
People like Mitchell are often overlooked, even with sophisticated talent management systems. Over two decades of work with more than 300 organizations, we have found that 3-5% of people in a typical network account for 20-35% of the value-adding collaborations. Yet when I compare my list of the Mitchells—often hundreds and sometimes thousands of central connectors distributed through an organization—against the company’s list of who they see as top talent, there is typically less than a 50% overlap. Among other problems, this means that many people making the most significant collaborative contributions are not getting recognized, and they often burn out and leave. Identifying these people is the first step to leveraging and supporting valuable, hidden talent.
The petroleum company ONA revealed another common opportunity for improvement—bridging silos. Here the production division was clearly disconnected from the rest of the organization. It turns out this was an ill-fated outcome of a decision to physically move this group two floors up in a building. The change created an invisible disruption to decisions that previously had been made in person in the hallway. This sounds minor until you realize that the high fixed-asset cost structure of this business meant they were losing millions of dollars a monthdue to these new hidden delays!
Of course, the idea is never to connect all people in a network; we are all overwhelmed with collaborative demands as it is. But without exception, network analysis reveals specific collaborative silos across functions, physical distance, capabilities and other dimensions of organizations that either undermine scale efficiencies or deter innovation possibilities.
A third opportunity for the petroleum company lies in the peripheral people in the network. Mares, the SVP, was only well-connected to two people, who were in the unit he was promoted from. He was not nearly as engaged in decision-making as he should have been. This is a common trap—very often people are promoted up in an organization yet 60-70% of their trusted relationships remain back where they came from. Right when they need a broader network to make effective decisions, this anchoring back into a narrow sphere kicks in and undermines success.
Sutherland, also on the edge, was a very expensive hire. The organization had spent nearly a year wooing him away from a major competitor. But once he was in the door, they did absolutely nothing to help him integrate into the network, and he quit six months in. Both these patterns are predictable network traps as people join new organizations or are promoted from within.
ONA Can Amplify Traditional People Analytics and Talent Management
Leading organizations increasingly combine network analysis with traditional people analytics for a more holistic view of the inner workings of their organization.
ONA can identify peripheral network members whose contributions go untapped. My research shows that in companies with strong cultures, it can take 3-5 years for newcomers to become as connected as high performers. But this does not have to be the case; we’ve also shown that a new person can replicate the connectivity of a high performer in 9-12 months with fairly simple role transition and newcomer integration practices.
At the other extreme, some employees can be too connected. 15-20% of employees in most organizations we’ve assessed fall into this category, and it is not a good thing. Being collaboratively overloaded leads to performance problems, burnout and departure—and not just of the overloaded individual. Attrition rates of those connected to an overwhelmed person can be as much as 200% higher than average. This risk is often not picked up by traditional engagement surveys or performance systems. Using ONA, HR can help reduce the collaborative burden on those that are too connected. Optimizing collaboration networks and practices in this way can retrieve 18-24% of wasted collaborative effort.
ONA can also improve employee turnover and retention. Again, many assume that a bigger network leads to better performance and lower turnover, but in fact those with larger networks are often more likely to leave in the first four years. Rather, success requires building the right network at the right time.
ONA and other network analytics tools may also map highly nuanced interactions, revealing people who create energy and a sense of purpose. These are ideal leaders and succession candidates. Recent research shows that generating trust, purpose and energy in networks drives successful innovation, execution, scale and well-being. And, when organizations combine ONA with performance data such as ratings, patent counts and revenue, they find that high performers are those whose networks are optimized for their role and objectives.
Furthermore, as organizations strive for greater diversity and inclusion, ONA can help provide a road map for keys to inclusion in truly novel ways. We can measure inclusion by tracking the degree diverse views are included at points of influence and decision making. We can also identify informal influencers who and recognize hidden stars who may be overlooked or excluded by the norms and unconscious bias within the organization.
ONA Can Create Data-Driven Solutions to Critical Challenges
Seeing the patterns of information flow, decision making, influence or energy across groups, teams or functions may be interesting, but the real magic comes from what leaders and companies can do with this information to promote rapid innovation and propel organizational effectiveness.
Companies put ONA into action to address specific challenges, including:
- Driving organizational change and agility. ONA can help identify critical points where improvements in collaboration can generate business value while also providing a road map of the best way to drive change through key network influencers or by addressing very targeted silos. Targeted and actionable changes are identified by comparing “as is” patterns of collaboration with future state or desired patterns required for a company to execute strategically. Organizations can then facilitate cross-silo connections, deploy expertise more effectively and engage influencers to ease acceptance of change. Read case study of a global restructuring of the IT function in one of the world’s largest engineering and construction companies.
- Promoting rapid innovation. ONA can assess information flow, new idea generation, problem solving and decision-making interactions. Findings can then reveal critical points to promote connectivity to drive strategic innovation, investments in network that can spur emergent innovation, ways to improve effectiveness of targeted groups like new product development teams and identify people who play roles of network brokers and connectors. With this data, organizations can prompt emergent innovation by removing silos, combining expertise and accelerating decision-making. Read case study of innovation and reduced product development cycle time in a Fortune 500 pharmaceutical company.
- Driving revenue growth. ONA can map revenue producing collaborations by size of transaction to help organizations understand ways to structure and incent sales in collaboratively intense work. Alternatively, patterns of information flow and collaboration can be tied to revenue production and other metrics of velocity or account penetration. These insights can reveal differences in team connectivity, identify people who are well positioned but under-utilized to assist with sales, show hidden aspects of the business development cycle, or flag network behaviors of high performers. Results illuminate points in the network where improved collaboration would produce better client solutions or new revenue opportunities. Read case study of a large consulting and technology company continuing to grow in a difficult business environment.
- Improving performance through collaboration. ONA can assess patterns of collaboration across functions, locations and expertise. By understanding the depth and intensity of collaboration, organizations can reduce collaborative overload on central people/roles/units in the network, integrate expertise on the edge of the network, break down silos that are undermining performance and better leverage top talent. Read case study of strategic collaboration and talent integration at one of the world’s largest electronic manufacturers.
- Speeding merger integration. ONA can assess connectivity between “legacy” and “new” groups, identify opinion leaders, and map beliefs, goals and priorities. Insights allow leaders to be much more effective in their retention strategies—often avoiding the invisible knowledge losses in the network due to over-focus on formal structure. In addition, the analytics allow for much more effective integration by targeting and bringing together well-connected people on each side of the merger in specific kinds of forums. These targeted efforts can decrease time to integration three-fold by enabling leaders to not shoot blindly or just pick their favorites. Read case study of a global consumer products company that overcame challenges of multiple mergers.
ONA-driven strategies tend to require minimal additional resources. The focus is on tracking and encouraging a small number of pivotal relationships and targeting interventions where they are proven to make a difference.
Want to learn more about ONA and application of network science? Read The Collaborative Organization: How To Make Employee Networks Really Work (Sloan Management Review) or A Practical Guide to Social Networks (Harvard Business Review). Consider viewing our free ONA for Business Success Virtual Course or contact us to learn more about customized network analytics to promote rapid innovation and propel organizational effectiveness.
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