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Measuring Success in Open Source Projects - OW2Con 2017

Measuring Success in Open Source Projects - OW2Con 2017

Slides for "Measuring Success in Open Source Projects" talk at OW2Con 2017

Bitergia

June 27, 2017
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  1. Measuring Success in Open Source projects Manrique López @jsmanrique jsmanrique

    at bitergia dot com https://speakerdeck.com/bitergia OW2Con, Paris, June 2017
  2. /goals “...accelerate open technology development and commercial adoption…” “...global development,

    distribution and adoption of the OpenStack cloud…” “...open, collaborative software development projects…” Put your project logo here Put your project vision/purpose here “...promote the development of open-source middleware, generic business applications, cloud computing platforms and foster a vibrant community and business ecosystem…”
  3. Measuring Success “Without data, you are just another person with

    an opinion” W. Edwards Deming Some examples
  4. /community dependency KPIs Onion model ASF Pony factor Bitergia Elephant

    factor Bitergia Zapata factor Linux Kernel Zapata factor ~ 200 Bitergia United Fruit Company factor Linux Kernel UFCo factor ~ 10 Linux kernel ownership analysis: linux.biterg.io 7 core ~ 40 regular ~ 85 casual Pony factor: 1 Elephant factor: 2
  5. Measuring Success “If you can not measure it, you can

    not improve it” Lord Kelvin The Bitergian way
  6. /collecting data “Collecting data is only the first step toward

    wisdom, …” grimoirelab.github.io 100% free, open source software
  7. /measuring “Collecting data is only the first step toward wisdom,

    but sharing data is the first step toward community” Henry Louis Gates Jr., IBM/Linux Commercial Community Activity Performance
  8. /measuring “Collecting data is only the first step toward wisdom,

    but sharing data is the first step toward community” Henry Louis Gates Jr., IBM/Linux Commercial Community Activity Performance Transparency Awareness Governance support Motivational
  9. /methodology Governance -> Goals <- Questions <- Metrics 1. Develop

    a set of corporate, division and project business goals and associated measurement goals for productivity and quality 2. Generate questions (based on models) that define those goals as completely as possible in a quantifiable way 3. Specify the measures needed to be collected to answer those questions and track process and product conformance to the goals 4. Develop mechanisms for data collection 5. Collect, validate and analyze the data in real time to provide feedback to projects for corrective action 6. Analyze the data in a post mortem fashion to assess conformance to the goals and to make recommendations for future improvements
  10. /take care “Human beings adjust behavior based on the metrics

    they’re held against. Anything you measure will impel a person to optimize his score on that metric. What you measure is what you’ll get. Period”. You Are What You Measure by Dan Ariely