Key Project Metrics That Predict Success
Identify which project metrics are genuinely predictive of success and which should be disregarded as vanity metrics.
What is this page about?
An explainer of the project metrics that predict success, opening with Flickr's lines-of-code leaderboard bloating its codebase while a focused Instagram overtook it, a vivid case of Goodhart's Law. It distinguishes leading from lagging indicators and covers five categories of project metrics (schedule and velocity, quality, scope and requirements, risk and issue, and team health), the Goodhart and vanity-metric problems, and how to select metrics that measure outcomes rather than gameable outputs.
What has been corrected on this page?
Every accepted correction to this page is recorded with the exact change, so readers can see how the page improved over time.
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The 6,570x DORA figure describes lead time/recovery speed; elite performers' change failure rate is only ~7x lower.
Before6,570 times fewer failures
After7 times fewer failures
Why: Verified live: body text already reads 'deployed code 973 times more frequently than bottom quartile organizations, with 7 times fewer failures'. FAQ field decoded and checked, no reference to the 6,570x figure. No further action needed.
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