Effectively manage team collaboration while identifying talent gaps


  • Difficulties to hire and retain engineering talents
  • Inability to proactively identify knowledge gaps
  • Lack of effective communication and reporting with engineering stakeholders
  • No data to build cases for new headcounts


  • Spot learning development opportunities for your engineers
  • Get tangible data to advocate for your team members
  • Understand effective work and collaboration patterns
  • Build strong cases for new headcounts and work balance between individuals and teams

Expertise Management

Expertise is defined by the level of knowledge and experience in specific technology areas such as Machine Learning & AI, Security, Distributed Systems, etc. Knowing who the true Machine Learning or Security experts are based on the analysis of their code rather than subjective measures can be extremely valuable to companies in the context of re-organization, hiring or mentoring projects. source{d} dashboards can help IT executives align company-wide objectives with engineering talents and interests.

Examples of questions you should have the answers to:

  • Do developers on my team have the right skill set?
  • What are the mentorship opportunities I can give to my senior developers?
  • What should be the profile of my next hire?

Examples of metrics you could be tracking:

  • Top Areas of Expertise
  • Fastest Growing / Declining Expertise
  • Code ownership
  • Expertise Misalignment

InnerSource & Collaboration

Companies are starting to realize that they would benefit from applying the culture and values from Open Source Communities to teams behind companies firewalls. This engineering initiative is called InnerSource and consists of creating a welcoming environment where code development, discussions and decisions are all happening in the open. With source{d}, you can easily measure and manage collaboration and mentorship opportunities.

Examples of questions you should have the answers to:

  • How effective are we at cross-team / company collaboration?
  • Are teams collaborating using each other's code and contributing back (outside of their core team)?
  • Is code being re-used?

Examples of metrics you could be tracking:

  • Per-project code ownership plots
  • Co-occurrence of developers across different projects
  • Share of repositories with missing documentation

Resource Allocation & Attrition

Hiring and retaining engineering talents is a challenge that most enterprises face. Data is what engineering leaders need to inform their resource allocation decisions. With source{d} they can not only build cases for new headcount but also measure attrition and HR costs and ROI of specific IT initiatives.

Examples of questions you should have the answers to:

  • How many employees have left or changed teams overtime?
  • Are my engineering headcounts allocated to the most important/urgent projects?
  • Is the work evenly distributed across individuals and teams?

Examples of metrics you could be tracking:

  • Internal / External Attrition or Churn Rates
  • Cost breakdown by activity
  • Workload Balance

How source{d} works for you

Engineers & Researchers


From data retrieval, language analysis and machine learning on code tools, datasets and models, the source{d} stack can be helpful for many software engineering use cases.

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Engineering Managers


With a built-in UI and a great user experience, source{d} delivers an enterprise-ready data platform to shift your IT budget from maintenance to innovation.

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Business Leaders


The source{d} platform allows you to modernize your entire software development life cycle so that your comapny can focus on providing more value to your customers quicker.

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