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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