Dynamic (Social) Networks

Social network theory models organizational communication and work
patterns. The core idea is that information and influence flow between
people or groups (nodes) via relationships such as reporting structures
or conversational and e-mail interactions (arcs). Analyzing such network
models highlights problems such as isolated or over-burdened employees or
groups. Resolving these issues can drive major improvements in productivity,
collaboration, and innovation. Network theory has also been applied successfully
to diverse phenomena such as the Internet, academic publishing, terrorist groups,
and the spread of infectious diseases.

Numerous software tools exist for depicting networks graphically and
summarizing their structures via statistical metrics. However, most of these
tools are static and homogeneous: they tend to capture network states at specific
points in time, where nodes and arcs are limited to single types of things,
such as individuals vs. organizations vs. locations or communication
vs. funding links.



ForeTell® solution
Our ForeTell Dynamic Network solution (DynNet) overcomes both constraints: the true power of networks lies in dynamic analysis and heterogeneity. In essence, ForeTell allows you to study your networks as if you were viewing a continuous movie rather than isolated photographs. Dynamic models reflect real world influences that cause networks to change, including situational forces and trends, disruptive events such as mergers or layoffs, and personal/group behaviors. They can also project the likely consequences of proposed strategies to modify networks, such as communication or compensation programs. Our ForeTell solution also supports disparate links and actor types in a single model.

  • Capture your knowledge of internal or competitor networks in a dynamic, actionable format
  • Project and assess network changes in advance from assumed scenarios and intervention strategies
  • Monitor and tune network structure on an on-going basis

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