Generation is becoming cheap. Verification is becoming strategic.
The next analytics bottleneck may not be creating a metric, model, or dashboard. It may be proving that the output still means what the business thinks it means.
Consider a global margin KPI generated and deployed quickly. The code can be valid. The pipeline can be green. But a small semantic change - such as how cancelled offers are treated - can materially change the decision the KPI supports.
That is not a generation problem. It is a verification problem.
My proposed V.I.G.O.R. check for analytics delivery:
V - Verifiable: can another person reproduce the result?
I - Impact-rated: what decision could this change?
G - Governed ownership: who owns the business meaning?
O - Observable divergence: how will we detect drift from expected logic?
R - Release-controlled: can material changes be reviewed before production?
Governance should travel with delivery. That does not mean governing every change equally. It means putting stronger verification where the cost of being confidently wrong is highest.
What would you add to V.I.G.O.R. for enterprise analytics?
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