Why Your Company’s Data Is Always Wrong (And How to Fix It at the Source)

You just spent $200k on a data quality tool. Six months later, your dashboards are still wrong.

I see this every month:

• A company buys a shiny “data observability” platform.

• Engineers spend weeks running cleansing scripts.

• Executives sit through another round of dashboard reviews.

And still — the CFO says: “I don’t trust these numbers.”

By then, the tool gets blamed. The engineers get frustrated. And the leadership team quietly drifts back to Excel.

The real problem?

You don’t have a data quality problem.
You have a business process problem.

Bad Data Is Born Upstream

Dashboards don’t break themselves. Pipelines don’t spontaneously corrupt.

Bad data starts where people and processes collide:

• A sales rep skips CRM fields to close a deal faster.

• Finance adjusts revenue in Excel before the board meeting.

• Marketing defines “lead” differently than Sales.

Your data team is mopping the floor while the pipe is still leaking. No $200k tool fixes that.

(If this sounds like your company, see our guide: Why BI Dashboards Fail Adoption)

Why Expensive Tools Don’t Save You

Data quality software isn’t useless. But it’s like buying a fire alarm for a house without walls.

Here’s why tools won’t save you:

• They don’t fix inputs. If sales isn’t incentivized to complete CRM records, no script can fill the gaps.

• They don’t fix definitions. If Finance and Sales can’t agree on “revenue,” no monitoring tool will reconcile it.

• They don’t fix ownership. If no one is accountable, issues just get passed back and forth.

This isn’t a tech issue. It’s an operating model issue.

(For more on ownership and reporting, read: Where Should the Data Team Report?)

The Playbook: How to Actually Fix Bad Data

Step 1: Go to the Source

Don’t start with dashboards. Sit with the people entering data — sales, finance, ops. Watch their workflows. You’ll identify 80% of root causes in a single afternoon.

Business Impact: Faster fixes, fewer downstream escalations, millions saved in rework.

Step 2: Assign Owners and Stewards

Sales owns sales data. Finance owns financial data. Pair them with data stewards to enforce definitions and connect business to IT.

Business Impact: Accountability cuts data firefighting time in half.

(Related: The ROI of Data Governance)

Step 3: Change Incentives

Policies don’t change behavior — incentives do.

• Tie part of sales comp to CRM completeness.

• Ban Excel “fixes” in board prep.

• Make data accuracy a measurable KPI, not an IT aspiration.

Business Impact: Aligns executive trust with frontline behavior.

Step 4: Profile and Prioritize

Don’t boil the ocean. Profile datasets, identify the riskiest ones, and fix in ROI order: financial reporting, compliance, revenue-critical.

Business Impact: Avoids wasted months fixing data nobody uses.

Your data isn’t wrong because of a warehouse problem. It’s wrong because of messy processes, broken incentives, and no ownership.

No $200k tool will fix that.

If you’re ready to stop firefighting and finally get executives to trust the numbers, it starts with fixing data at the source.

Schedule a Data Strategy Assessment today and see how to rebuild trust in 90 days?