Data Governance and the Single Source of Truth

The Myth of one truth

Companies often come to us because their reporting doesn’t add up.

Dashboards contradict each other, KPIs are inconsistent, and the root cause is almost always assumed to be technical.

In kick-off workshops, I like to start with a simple question:

“Can you please define revenue?”

The answers are almost always eye-opening:

• Finance: net revenue after payment received
• Sales: accrued revenue, discounts included or not, depending on context
• E-commerce: order intake before fulfillment

Three stakeholders. Four definitions. All correct. But nobody means the same thing. (And let’s not even get started on contribution margins ;) ).
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The Real Problem

The issue is rarely broken pipelines or faulty dashboards. The real problem is that every department has its own valid perspective. But those differences were never explicit.

The result? Parallel truths. Finance reports under IFRS. Sales optimizes for forecasts. Marketing attributes campaign-driven revenue. Everyone talks about “revenue,” but the numbers can’t be compared.

That’s not a technical problem. It’s a governance issue.
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What Governance Really Means

Data Governance doesn’t mean forcing everything into one number. It means making differences visible, structured, and transparent

• Gross Revenue, Net Revenue, Order Intake, each definition clearly documented
• A KPI set that everyone knows, understands, and accepts‍
• Accountability: Who owns which KPI, in which context?

In one project, I came across 12 different revenue definitions across seven business units. My personal record. In the end, we consolidated them into 5. Rarely does it come down to a single number. But each was documented, consistently named, and contextually clear. Ideally, organizations agree on one primary KPI as a reference point. The rest are managed as clearly defined subsets.

Single Source of Truth. Rethought

The famous Single Source of Truth is often misunderstood. It’s not about one magical number. It’s about ensuring that everyone works with a consistent, agreed KPI set. One that is clearly defined, consistent, and reliable across all reports, dashboards, and analyses.

Not: “Revenue = one number.”
But: “Revenue = multiple variants, but each is documented, consistently named, and transparent to everyone.”

The Political Dimension & Conclusion

The technical side, pipelines, KPI definitions, semantic layers, is one thing.
The real challenge lies on the organizational level.

Because once it becomes clear that departments have been working with different truths for years, tough questions arise:

• Who defines “revenue”?
• Which department is accountable?
• How do we handle deviations going forward?

This friction is valuable but also delicate. Governance forces organizations to make definitions and responsibilities explicit. What was once implicit and a constant source of misunderstanding becomes visible, documented, and manageable.

This is often the hardest part of BI projects: realizing that teams have been talking past each other for years, and that even bonus models or performance targets may have been tied to conflicting definitions.

That’s why we prepare projects for this political reality from the start: past misunderstandings must not undermine trust or cohesion. On the contrary. They’re an opportunity to clear out legacy issues and make performance measurement more objective.

And that, ultimately, is the true essence of being data-driven:

Not just making decisions based on numbers, but ensuring that everyone is talking about the same, clearly defined numbers.

For governance to succeed, it requires C-suite involvement and a clear organizational anchoring of KPIs. Ownership must be explicit. Otherwise, the consolidation effort will collapse at the first sign of change.

Final takeaway:

The truth in BI is never one number. The truth is governance