#241 Data Product Success Metrics – A Kinda Deep Dive – Mesh Musings 51

Key summary points:

  • At the start, it’s more important to start measuring than it is to measure the right things. Do NOT let analysis paralysis hold you back.
  • Similarly, your success metric measurement framework will probably suck to start. Oh well, get to measuring.
  • Create a framework and tooling/platform capabilities – where necessary/useful – to make measuring and reporting against success metrics simple. That framework should be about defining the metrics and especially how to measure, not what success looks like for individual data products.
  • Use fitness functions
  • Good metrics to consider in order of usefulness: user satisfaction, user value, data quality, time to business decision, delivery to expectations, time to update (can be squishy), and usage

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All music used this episode was found on PixaBay and was created by (including slight edits by Scott Hirleman): Lesfm, MondayHopes, SergeQuadrado, ItsWatR, Lexin_Music, and/or nevesf

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