Want AI to run your SaaS FP&A, but not sure your data can handle it?

In episode #393, Ben Murray breaks down a simple 1-to-5 scale for rating your four key SaaS finance data sources: financial, bookings, people, and customer/revenue data. Every finance team wants AI analysis on top of their SaaS metrics, but AI is only as trustworthy as the data underneath it. If your exports are a mess, your GL coding is inconsistent, or your close depends on heroics every month, AI will just produce bad answers faster. This scale shows you exactly where you stand and what it takes to get to the top of the mountain.

• Score each of your four key SaaS finance data sources from 1 (unusable) to 5 (operational) and see where you're actually blocked.
• Learn the difference between raw, structured, and reconciled data, and why that difference decides whether you can trust AI output.
• Understand why a 3 is good enough to start: get the end-to-end process running mechanically, then iterate on data quality.
• See what 'operational' looks like: reconciled data, a named owner, documented steps, and a repeatable process built into your monthly close checklist.
• Use this scale as your AI readiness checklist before rolling out AI across your finance or FP&A team.

Tune in, grab a pen, and rate your data before you trust AI with your next board package.

Resources Mentioned

• Live SaaS Metrics Sprint (7-week live course): https://www.thesaasacademy.com/saas-metrics-implementation-sprint-sept-2026