Data Farm
Written by: David Carneal – Digital Efficiency Consulting Group – DECG
Read Time: 3 min
If anyone can quietly change KPI logic, the KPI is not a KPI. It’s a suggestion.
Governance doesn’t have to be heavy. It just has to exist. The point is tamper resistance and auditability: you can see what changed, who changed it, and why.
When governance is missing, your organization pays a steady tax: re-explaining metrics, rebuilding reports, and re-litigating the same definitions.
The two goals of governance
Governance sounds like a 47-page PDF nobody reads. Let’s translate it into two goals you can defend in any meeting.
If your governance doesn’t support these goals, it’s paperwork, not control.
- Goal 1: Tamper resistance
- Raw data is protected from manual edits.
- Transformations are versioned and reviewed.
- Certified datasets are clearly marked.
- Goal 2: Auditability
- You can trace KPIs from dashboard back to source records.
- You can answer who changed what, when, and why.
- You can reproduce last month’s numbers without archaeology.
Separation of duties (without making it painful)
One of the simplest wins is separating who can ingest data, who can transform data, and who can certify data.
This isn’t distrust. It’s how you prevent accidents and keep a clean audit trail. Small teams can do this with process, not headcount.
- Practical roles (small team friendly):
- Data owner: approves definitions and meaning.
- Data engineer/analyst: builds transformations under review.
- Dashboard creator: uses certified datasets and labels custom work.
Version control for KPI logic (yes, even if it’s boring)
If KPI logic changes, it should be a visible change. That means a documented reason and an approval step.
You don’t need a giant committee. You need a small review habit. Ten minutes is enough to stop silent rewrites.
The win is consistency: the KPI doesn’t mutate because someone needed to “make it match” ten minutes before a presentation.
- Minimum viable review:
- What changed (definition, filter, mapping, timing)?
- Why it changed (bug fix, definition clarity, business policy)?
- Who approved it (named owner)?
- When it takes effect (effective date)?
Monitoring and alerts (stop finding out in meetings)
A governed system finds issues early. If your first signal is “the dashboard looks weird,” you’re paying a premium for surprise.
Monitoring doesn’t have to be fancy. Start with volume and reconciliation checks. Add anomaly alerts when the basics are stable.
- Simple monitors that pay for themselves:
- Ingestion success/failure + row count checks.
- Daily volume trends (spikes, drops, missing days).
- Key reconciliations (revenue tie-outs, shipment counts, inventory movements).
- Data freshness checks (last updated timestamp).
Governance checklist you can use tomorrow
Run this checklist against your current setup. It’s short on purpose. Long checklists get printed and then used as coasters.
- Governance checklist:
- Raw zone is write-protected for humans.
- Ingestion is logged and monitored (success, fail, volume).
- Transformations are versioned (no silent edits).
- KPI definitions have named owners.
- Executive dashboards pull only from certified datasets.
- Custom metrics are labeled and not mixed with certified KPIs.
The payoff: faster diagnosis, faster decisions
Governance pays off the first time a number looks wrong and you can answer “why” in minutes. It pays off the first time a system changes and you can reprocess cleanly.
It also reduces the single point of failure: the one person who understands the spreadsheet logic and is currently on vacation with their phone on airplane mode.
CTA: Pick one KPI and require any definition change to go through a simple review. Add one basic monitor (row count or freshness) this week. If changes can’t happen quietly and issues show up early, trust starts to rebuild.

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