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Organizational Influence

Question: How much influence does an organization have on an open source community?


Organizational Influence is a measure of the influence that an organization has on an open source community. An organizations may influence the direction of a project, signaling some level of control within a community. This equates to the level of influence an organization has over the development trajectory of an open source project that it contributes to and has a vested interest in.


An organization can have influence in open source projects. The measure of an organization's influence can be enlightening on its own or serve as an opportunity to show growth in an organization's influence over time. This metric can help an open source advocate in an organization justify continued funding and support for engagement. This metric can also help open source maintainers track and measure organizational influence to add legitimacy to their project, and monitor the level of control by individual organizations. An organization's influence may also serve as a signal of how easy or difficult it may be for new members to contribute to an open source project.


Some specific examples to consider when measuring organizational influence include:

  • How many organizational members are contributing to a project - contributors. It can be understood as a ratio of (number of contributors from each organization with more than one contributor)/(number of contributors)
  • Level and types of contributions by organizational members
  • Organizations that are contributing change requests at a high rate in proportion to the community’s level of activity. For example, one standard deviation or less of other contributing organizations. Related to organizational diversity
  • Organizational members on the technical steering committee
  • Organizational members on governing board
  • Organizational members in project maintainer roles
  • Organizations sponsoring an open source project as a proportion of the total

Tools Providing the Metric

  • Augur
  • GrimoireLab


  • Sean Goggins
  • Matt Germonprez
  • Vinod Ahuja
  • Kevin Lumbard
  • Lawrence Hecht
  • Matt Snell
  • Dhruv Sachdev
  • Elizabeth Barron
  • Matt Broberg
  • Stephen Jacobs

To edit this metric please submit a Change Request here:

To reference this metric in software or publications please use this stable URL:

The usage and dissemination of health metrics may lead to privacy violations. Organizations may be exposed to risks. These risks may flow from compliance with the GDPR in the EU, with state law in the US, or with other laws. There may also be contractual risks flowing from terms of service for data providers such as GitHub and GitLab. The usage of metrics must be examined for risk and potential data ethics problems. Please see CHAOSS Data Ethics document for additional guidance.

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