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Organizational network analysis (ONA)

Measure how collaboration in your organization really flows — beyond the org chart. Evidence-based, measured and GDPR-proof.

What is organizational network analysis?

Organizational network analysis (ONA) is a method that measurably maps the actual collaboration and information flows in an organization. Where the org chart shows who reports to whom, ONA shows who works with whom: along which paths information and decisions really travel, where they get stuck, and which connections make the difference.

The gap between those two pictures is almost always large. Your org chart isn't broken — your lens is outdated: the formal structure is a photo of intentions; the network is the film of what actually happens.

What ONA makes visible

GDPR-proof, by design

Measuring collaboration touches personal data, so privacy is not a disclaimer afterwards but a design principle up front:

ONA is a calibration instrument, not a control instrument. That distinction matters legally — and it determines whether the organization trusts the results enough to act on them.

From measurement to decision

A network map is not a goal in itself. The value is in what follows: data → insights → intervention. The analysis tells you where a targeted intervention creates the most movement — which connection to restore, which node to relieve, which silo needs a bridge. Then you measure again and adjust. In part 2 of our org-chart series we describe that approach in detail.

Within our broader approach — The Organizational Brain and Shatter · Rewire · Activate — ONA is the diagnostic instrument that determines where we intervene: precisely on the neurons that are stuck, leaving alone everything that works.

Shatter Rewire Activate

When is ONA the right instrument?

Typical triggers in organizations of 100 to 500 people: a merger or strong growth after which nobody oversees the collaboration fabric anymore; decision-making that slows down without an identifiable cause; departments working past each other; or a planned change where you want to know in advance where it will hit resistance or overload. Not sure whether ONA fits your question? That's exactly the kind of conversation we're happy to have, no strings attached.

Frequently asked questions

What is organizational network analysis (ONA)?

Organizational network analysis is a method that measurably maps the actual collaboration and information flows in an organization: who works with whom, where information flows get stuck, which nodes are overloaded and which connections are missing. It shows the real network behind the formal org chart.

Is organizational network analysis GDPR-compliant?

Yes, when set up properly — and for us that's a design principle, not an afterthought. We analyze metadata about collaboration, never the content of messages. Results are aggregated and pseudonymized, the analysis happens at team and workflow level rather than on individuals, and purpose limitation and transparency towards employees are settled up front.

How is it different from an employee satisfaction survey?

A satisfaction survey measures how people feel; an organizational network analysis measures how the work actually flows. Both are useful, but ONA answers questions a survey cannot: where are the bottlenecks, which teams are islands, and who connects the organization without the org chart showing it.

Are individual employees assessed?

No. ONA is a calibration instrument for the organization, not a control instrument for individuals. The analysis happens at team and workflow level, results are aggregated, and no individual performance judgments are attached. That is essential for GDPR compliance and for the trust you need to act on the results.

What does an organizational network analysis concretely deliver?

An evidence-based map of how collaboration really flows, and from it: the bottlenecks that slow decision-making, the silos that block innovation, the overloaded key people who represent a continuity risk, and the places where a targeted intervention creates the most movement. From data to insight to intervention — then re-measure to see whether it works.

Further reading

Related questions

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