Data teams build pipelines. CFOs build forecasts. In theory, they’re working toward the same goal: clarity, truth, alignment. In practice, they’re often quietly at war.
It’s not open hostility -just a low-grade conflict that simmers inside every growth-stage company. And it’s costing organizations real money, real insight, and real operational efficiency.
Why the Disconnect Exists
Finance and data teams don’t actually disagree on outcomes. They disagree on inputs, definitions, and ownership.
Here’s what typically happens:
- The finance team builds its model in Excel. Metrics are fixed, clean, and traceable -but sometimes lagging and disconnected from product reality.
- The data team runs its own version of the truth, often sourced from the warehouse. It’s live, dynamic, and messy -but tied to actual user behavior.
Each side believes their version is right. Each side is technically correct. And nobody is working from the same playbook.
This leads to recurring tension points:
- Revenue doesn’t match across dashboards.
- “Churn” has three different definitions depending on the audience.
- Finance doesn’t trust product analytics, and data doesn’t trust the board deck.
The result? Weeks lost to reconciliation. Confusion over what’s real. And a default to whichever team can shout louder -or attach their slide to the CEO’s calendar first.
Who Owns the Metrics?
This is the central unspoken fight: Who defines the numbers that run the business?
Data teams see themselves as the system of record. They built the pipelines. They know how the metrics are generated. They’ve written the dbt models.
Finance teams see themselves as the final gatekeeper. They sign off on earnings calls, investor updates, and board materials. They control the narrative.
When these two worlds don’t coordinate, you get shadow metrics and metric theater:
- Finance reworks active user definitions to support a revenue forecast.
- Data teams publish cohort charts that undermine financial targets.
- Internal stakeholders ping both sides and cherry-pick whichever number fits their OKRs.
And the kicker? The real risk isn’t disagreement. It’s false agreement.
When both teams think they’re aligned -but aren’t -strategic decisions get made on a foundation of drift.
What Alignment Actually Looks Like
You can’t fix this with another Slack channel or a shared dashboard. You fix it with structure, incentives, and shared definitions.
Here’s how high-functioning orgs are solving the CFO-vs-data standoff:
- Joint Metric Ownership
Create a working group -not a forum, a working group -that includes leaders from both data and finance. They co-own every critical business metric (ARR, churn, CAC, margin) and document exactly how it’s calculated. The final model should be signed off by both sides. - Centralized Data Dictionary
Every investor-ready number should be backed by a plain-English, SQL-accessible source of truth. If there are multiple versions (e.g. “active user” by engagement vs. by payment), define when and why each is used. No ad hoc definitions allowed. - Metric QA Pipelines
Just like you QA your product, QA your metrics. Build automated checks into Looker or dbt to flag when definitions deviate or data falls outside expected bounds. Let both teams own the alerting. - Embedded Analysts in Finance
Don’t silo your analytics team. Assign a data analyst (or engineer) directly to finance. Their job isn’t just pulling data -it’s building bridges, pressure-testing assumptions, and surfacing inconsistencies early. - Forecast vs. Actual Reviews
Once a month, run a forecast vs. actuals review -jointly. Treat misses as analytical breakdowns, not just financial ones. This builds shared accountability and trust in the models. - Mutual Tool Literacy
Finance should know how dbt works. Data should know how 3-statement models are built. You don’t need cross-functional unicorns -you just need basic fluency so both teams can collaborate instead of defend turf.
Why This Matters Now
In 2021, misaligned metrics just made for confusing all-hands meetings.
In 2025, they can tank your next round.
Investors today ask pointed questions. They expect coherence between product KPIs and financial plans. If your CFO and head of data can’t present a unified view, you’re signaling internal chaos.
Even worse, mismatched models mean you miss opportunities:
- You underinvest in segments that look unprofitable in Excel but are growing like crazy in the warehouse.
- You cut channels with long payback periods that were on track to be your best LTV cohorts.
- You chase the wrong KPIs -not because they’re wrong, but because you’re looking at different versions of reality.
Bottom Line
This isn’t about dashboards. It’s about control.
Until CFOs and data leaders start treating metrics as shared intellectual property -not territory to defend -this friction will persist.
The good news? The fix is cultural, not technical. But it starts with admitting the turf war exists.