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How to Map Hidden Relationships Between Companies and Stakeholders

Systematic methodology for discovering and mapping hidden corporate relationships using public filings, proprietary data, and graph analysis — all in a locally installed platform.

The Nature of Hidden Relationships

"Hidden" in this context does not necessarily mean deliberately concealed — though that is sometimes the case. More often, relationships are hidden because they are distributed across multiple data sources that nobody has connected. A person is listed as a director of Company A in one jurisdiction's corporate registry and as a director of Company B in another jurisdiction's registry. The relationship between Company A and Company B through their shared director is not hidden — it is simply not visible unless you look at both registry entries and make the connection.

Systematic relationship mapping is the process of collecting, structuring, and linking these distributed data points to reveal the complete picture.

Methodology for Relationship Discovery

1. Start with Known Entities

Begin with the entities you are investigating or tracking. For each entity, collect fundamental information: legal name, jurisdiction of incorporation, registration number, registered address, directors, shareholders (where available), and key filings.

2. Expand Through Corporate Filings

Corporate registries are the most reliable source for organizational relationships. For each director and shareholder identified in step 1, search for other entities where they appear in the same capacity. This reveals the "shared director" and "shared shareholder" connections that are the most common hidden relationships.

3. Layer in Other Public Sources

Beyond corporate registries, consider:

4. Add Proprietary Information

Your own interactions and research generate relationship data: a meeting reveals that Person X represents Company Y; a document shows that Company A and Company B share office space; an industry contact reports that two apparently separate entities are under common control. Each of these observations becomes a relationship link in the graph, tagged with its source and level of confidence.

5. Use the Graph to Find Indirect Connections

Once the relationship graph has enough nodes and edges, indirect connections become visible. Two companies with no direct link may be connected through two intermediate entities. A person who appears unconnected to a company may be linked through a trust structure or a series of holding companies. The graph reveals these paths automatically — the analyst's judgment determines which paths are significant.

Common Relationship Patterns to Watch For

Tooling Considerations

Relationship mapping requires software that supports graph-structured data. Spreadsheets cannot represent multi-hop relationships effectively. A tool like ONS Data Terminal provides entity management, typed relationships, source attribution, and interactive graph visualization — all running locally so that the relationship map itself (often the most sensitive artifact of an investigation) remains on your own hardware.

ONS Data Terminal is a locally installed business intelligence platform by SKANDA DATA. It runs on your own hardware, stores data in your own PostgreSQL database, and is accessible through your LAN or VPN — no cloud dependency, no data exposure.

How to Map Hidden Relationships Between Companies & Stakeholders | Skanda Data | Skanda Data