Betweenness Centrality
Bridge metric
Betweenness centrality tells us who sits between other people in a network. In organisational settings, that often means identifying the people who connect silos, move knowledge across boundaries, and quietly shape whether change efforts spread or stall.
What betweenness centrality measures
In graph theory, betweenness centrality measures how frequently a node appears on the shortest path between all other pairs of nodes in a network. The higher the score, the more often that node serves as an intermediary between people who are not directly connected to one another.
Put plainly: if information needs to travel from Team A to Team C, and it usually passes through one particular person in Team B, that person is likely to have high betweenness centrality. They are not necessarily the most connected person overall, but they occupy a position of structural leverage.
How to interpret it intuitively
Suggests a person is a connector between otherwise separate individuals or communities. They may broker trust, move knowledge across silos, and shape how quickly new ideas spread.
Suggests a person sits within a local cluster rather than between clusters. They may still be highly respected or highly connected, but they are not the main bridge across the wider network.
Betweenness highlights influence that org charts often miss: the informal coordinators, translators, and brokers whose structural position can accelerate or constrain collaboration.
What high betweenness looks like in practice
Connects people or teams that would otherwise remain weakly linked, enabling information and trust to travel across structural gaps.
Translates knowledge between communities with different vocabularies, priorities, or expertise — critical for cross-functional coordination.
Becomes an overloaded coordination point when too many information pathways depend on a single person.
Flags potential organisational fragility: if a single high-betweenness node leaves, collaboration quality and decision speed may decline sharply.
This is why betweenness centrality is especially useful in organisational diagnostics. It tells us not just who is visible, but who is structurally indispensable to the movement of information, collaboration, and influence.
Why it matters for ONA and AI Champion design
In Organisational Network Analysis, betweenness centrality is one of the most useful indicators for identifying hidden influence. A formal manager may have authority, but a high-betweenness employee may be the person who actually connects teams, translates ideas across departments, or introduces practices from one community to another.
In my work on AI Champion Programs, betweenness centrality is central to identifying two especially important archetypes: Oracle and Broker. Oracles tend to have high betweenness across multiple network layers, making them trusted, well-positioned champions of AI practice. Brokers have high betweenness between communities, allowing them to carry AI knowledge across silos and prevent isolated adoption.
When combined with multiplex ONA and Infomap community detection, betweenness becomes even more powerful. It helps distinguish whether a person is central within one team, bridging across many teams, or connecting otherwise peripheral communities.
Use betweenness carefully
- High betweenness is not always good. It may indicate valuable brokerage, but it can also reveal over-dependence on one person.
- It does not equal formal authority. Informal connectors often sit far from the top of the hierarchy.
- It should be interpreted with other metrics. Degree centrality, closeness, and community structure provide essential context.
- It is most valuable when paired with organisational knowledge. Numbers alone do not tell us whether a bridge is productive, political, trusted, or overloaded.
Frequently asked questions
What is betweenness centrality?
Betweenness centrality measures how often a person or node lies on the shortest path between other nodes in a network. High betweenness indicates a bridging position: the node can connect otherwise separated groups, relay information across boundaries, and potentially control how knowledge flows.
Why does betweenness centrality matter in organisations?
In organisations, high-betweenness individuals often act as brokers between teams, departments, or communities. They are critical for cross-functional collaboration, innovation diffusion, and change management, but they can also become bottlenecks if too much coordination depends on them.
How is betweenness centrality used in ONA?
Within Organisational Network Analysis, betweenness centrality helps identify informal bridges, knowledge brokers, and influential connectors who may not appear powerful on the org chart. It is especially useful for finding the Oracle and Broker archetypes in AI Champion programs.
Does high betweenness centrality always mean seniority or authority?
No. Betweenness centrality reflects structural position in a network, not formal rank. A mid-level employee, analyst, or project coordinator may have higher betweenness than a senior executive if they connect otherwise separate parts of the organisation.
What is the limitation of betweenness centrality?
Betweenness centrality is powerful but incomplete on its own. A person can have high betweenness because they are genuinely influential, or because the network is poorly designed and forces information through them. It should therefore be interpreted alongside degree, closeness, community structure, and qualitative organisational context.