Your question is Identify Delivery Risk Leading Signals. Take a moment with it on the right.
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You are an engineering manager for a B2B infrastructure design collaboration platform used by enterprise project teams to review models, issues, and design changes. Your organization tracks on-time delivery for quarterly roadmap commitments, and the last two quarters finished at 91% and 88% on-time, but leadership wants earlier warning before milestones are missed. In the current quarter, only 2 of 9 teams are officially red, yet cycle time has risen from 6.2 to 8.1 days, reopened defects are up 34%, and the share of work carrying over sprint to sprint has increased from 12% to 19% after a recent integration release and a platform upgrade. You need a metric framework that flags delivery risk before roadmap dates slip.
What signals would you define as leading indicators that a team is at risk before delivery slips, and how would you distinguish true risk from normal variation or temporary noise? How would you structure the metric hierarchy so leaders can diagnose whether the issue is planning quality, execution throughput, dependency management, or product quality?