Network Centrality Measures
Not all nodes are equal. Centrality measures reveal which employees, proteins, or websites actually control information flow—often invisible in formal hierarchies.
Different centrality measures capture different types of importance in networks: (1) Degree centrality - most direct connections, the node everyone knows. (2) Betweenness centrality - how often a node is a bridge; information flowing between others must pass through it. High betweenness = control over information flow but also bottleneck risk. (3) Eigenvector centrality - connected to other well-connected nodes. Google's PageRank uses this principle - pages linked by important pages are themselves important.
Business Application of Network Centrality Measures
Centrality measures identify critical organizational nodes: degree centrality finds popular connectors, betweenness centrality finds bottlenecks and information brokers, eigenvector centrality finds influencers connected to other influencers. Each has implications for resilience and efficiency.