Framework

A practical operating model for data quality.

The Perfect Data Framework turns data quality from an ad-hoc firefight into a durable program: clear roles, repeatable workflows, and measurable improvement.

Schedule a Call Roles
Ownership Repeatable workflow Trend-based KPIs Audit-ready evidence
Framework in one sentence

Identify defects with rules, assign ownership, fix root causes, and prove sustained improvement.

Guiding principle
If a defect repeats, the process failed—not the people. The framework is designed to reduce repeat failures.
See the software workflow Start with the rule library

The core roles

A simple role model that keeps work moving and prevents quality from becoming “everyone’s problem.”

See workflow

Analyst

Find, triage, and quantify issues
  • Reviews rule exceptions and impact
  • Determines severity and scope
  • Creates or refines rules and thresholds
  • Documents findings for fixers

Fixer

Resolve root causes
  • Owns remediation and prevention
  • Updates upstream processes and systems
  • Coordinates changes across teams
  • Confirms defects no longer recur

Executive

Align priorities and ensure accountability
  • Sets expectations and cadence
  • Unblocks cross-team remediation
  • Reviews trend KPIs and outcomes
  • Ensures ownership is maintained
Role clarity reduces repeat incidents
Analysts should not be fixing root causes. Fixers should not be guessing at impact. Executives should not be surprised at deadline time.

The operating workflow

A repeatable sequence that scales from a single report to an enterprise program.

1) Define and maintain rules
Rules represent “quality expectations” for critical datasets and reports.
2) Run scans on a cadence
Schedule checks around operational windows and reporting deadlines.
3) Triage and route issues
Analysts classify severity and assign to the right fix owners.
4) Fix root causes and verify
Fixers eliminate recurrence; executives review trend outcomes.

Cadence and governance

The framework works best with a lightweight governance cadence:

  • Daily/Weekly: triage exceptions, assign owners, validate fixes
  • Monthly: review trend KPIs, top recurring issues, coverage gaps
  • Quarterly: prioritize new monitoring areas and cross-team initiatives
  • Always: maintain ownership mapping and improve rule quality
Align on a rollout plan See how software supports this

What to measure

The framework focuses on metrics that drive action and reduce recurrence.

Metric What it tells you Why it matters
Exception volume How many defects are present Quantifies impact and prioritization
Recurrence rate How often the same issue returns Highlights root-cause gaps
Time-to-triage How quickly issues are classified Prevents “surprise” defects at deadline time
Time-to-fix How quickly root causes are eliminated Drives operational reliability
Coverage How much of the critical surface is monitored Shows program maturity and gaps
Top recurring issues The “repeat offenders” Directs executive attention to the highest leverage fixes

Want to implement the framework in your organization?

We’ll map your teams, define initial monitoring coverage, and propose a governance cadence that matches your reporting realities.

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