What’s the simplest way to show our CFO why fragmented customer billing data from SAP and Salesforce isn’t ready to use for accurate revenue forecasting?

Here’s a clear, pragmatic way to explain this to your CFO without jargon or hand-waving:

Use a short, simple example that makes the problem tangible.

Try something like this in your conversation or a one-slide visual:

Example: Why Fragmented Billing Data = Inaccurate Forecasts

Scenario:

• Customer XYZ has billing data in SAP and Salesforce.

• In SAP, they show $100,000 billed YTD.

• In Salesforce, they show $75,000 of invoices.

Problem:
When you try to forecast revenue, you get conflicting totals:

• If you sum them without deduplication, you report $175,000—which overstates revenue by 75%.

• If you pick just one system, you risk understating revenue or missing open invoices.

• If invoice dates or payment statuses don’t align, your cash flow forecast becomes impossible to trust.

3 reasons this isn’t ready for forecasting yet:

1. Duplicates: The same invoice can exist in both systems, with no shared ID to reconcile.

2. Inconsistent Timing: One system may show invoices as issued, while the other shows them as pending.

3. Incomplete Records: Some transactions only exist in one system, creating blind spots.

Simplest way to show this visually:

Make a table with 3 columns:

Result:

• Totals don’t reconcile.

• Statuses conflict.

• Forecasts are unreliable.

How to position it constructively:

“This is why we need a consolidation and reconciliation step before we can produce an accurate forecast. Otherwise, we’re either double-counting, missing revenue, or confusing timing—none of which supports reliable planning.”

Bottom line for the CFO:

Fragmented data looks complete at first glance, but without cleaning and mapping, every forecast is a guess—and a potentially expensive one.

This approach is fast, concrete, and shows exactly why the data isn’t trustworthy—no technical deep dive required.