What organizational network analysis is, why communication data is more reliable than surveys and management interviews, and what it means for acquirers focused on value creation
Most deal teams and operating partners are making structural decisions — resource allocation, org design, integration sequencing, team composition — using a combination of:
of post-acquisition value destruction is attributable to people and integration failure — often caused by decisions that severed informal networks sustaining revenue, delivery, or execution capacity
We clean and strip communication data from Microsoft 365, Google Workspace, and Slack to reveal only who communicated with whom and when. Building on decades of academic research, we then use statistical analysis to create ONA metrics — aggregated and anonymized to reveal the informal networks that drive organizations
| Conventional analysis | Organizational network analysis |
|---|---|
| Measures what people say they do. Subject to self-reporting bias. | Measures what people actually do. Based on observable, auditable communication events |
| Org charts show formal hierarchy. Real authority is invisible. | Maps where influence and authority actually concentrate, regardless of formal title |
| Key-people risk identified reactively, when individuals leave | Structural dependency mapped before it becomes a value event |
| Integration fault lines discovered during execution, when they are expensive to address | Structural incompatibilities between organizations visible before the integration plan is finalized |
| Months to field surveys and synthesise results | Structural insight in 2–4 weeks. No survey distribution |
| Transformation success or failure only becomes clear in P&L months later | Ongoing reviews identify adjustments needed — within weeks |
Organizational intelligence from network analysis connects to the financial metrics PE and strategic buyers track across the investment lifecycle
Sales velocity, ARR growth, NRR — driven by the structural conditions enabling commercial teams to execute
Operating margin, burn multiple — affected by siloes, bottlenecks, and management gaps
Revenue per employee, retention cost — shaped by where structural concentration creates dependency and departure risk
Integration cost and timeline — determined by whether informal networks mesh or clash
Customer churn, cost-to-serve — influenced by how well client-facing teams are structurally connected
The structural conditions that determine your returns are identifiable before they move the numbers
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