CDC Signoff Dashboard: Reports & Metrics

Reports and metrics

Reports & Metrics for CDC Signoff Dashboard focuses on critical violations trend, closure burn-down, owner SLA adherence. The goal is to convert issue observations into mechanism-backed closure decisions.

Reports must explain risk movement in critical violations trend, closure burn-down, owner SLA adherence, not just issue counts. A report is complete only when ownership and closure action are explicit.

Metric movement

METRIC TREND — critical violations trend, closure burn-down, owner SLA adherence

critical open issues
  ^
  |                target (0 critical)
  |              - - - - - - - - - -
  |          o post triage
  |      o initial run
  |   o baseline
  +--------------------------------------> review iteration

Always pair count trend with evidence quality trend.

Risk distribution

RISK HEATMAP — CDC Signoff Dashboard

severity
high   |  XX  X
medium |  XXX XX
low    |  XXX XXX
        +----------------------------> ownership readiness
         unassigned   in-progress   closed

Metric focus: critical violations trend, closure burn-down, owner SLA adherence

• Track critical violations trend, closure burn-down, owner SLA adherence by block, mode, and severity.

• Separate structural warnings from behavior-proven hazards.

• Show waiver age and owner SLA alongside raw counts.

• Store evidence links with each closure claim.

CDC/RDC deep dive

Signoff is an evidence governance problem across teams.

Concept diagram

CDC SIGNOFF LOOP

analysis -> triage -> fix/waive -> review gate -> dashboard

Metric graph

CRITICAL OPEN COUNT

week1 34
week2 22
week3 10
week4 0

Reports and artifacts

• critical by owner

• waiver quality

• review gate status

• closure trend

Mini case study

Pass rates improved while critical waivers aged out of policy; dashboard exposed hidden risk.

Debug branches

• Separate quality from quantity metrics

• enforce waiver expiry

• run gate checklists consistently

Senior review question

Ask: what evidence proves this risk is closed for silicon, not just tool-clean?

Key takeaways

• State crossing class, assumptions, and owner with every issue.

• Run structural and dynamic regressions after each fix.

Common pitfalls

• Treating all warnings as equivalent risk.

• Waiving issues without containment evidence.

• Skipping reset and reconvergence stress after CDC fixes.

Reading evidence