Confidence Levels & Data Gaps
Why every number in DiligenceDesk carries a Low/Medium/High badge instead of pretending to be precise — and how to read one.
Separation economics estimates are built on a mix of hard data (signed contracts, HRIS extracts) and judgment (how a customer will behave post-close, whether a vendor will renegotiate). Presenting all of that with the same false precision — a single number to the nearest hundred thousand — hides exactly the information a deal team needs most: which numbers to trust, and which to keep diligencing.
- High confidence
- Backed by a validated, primary-source input — a signed contract, a payroll extract, a finalized vendor SOW.
- Medium confidence
- Backed by a credible but not-yet-validated source — a draft SOW, a management estimate, an interim extract.
- Low confidence
- Backed by an assumption or incomplete data — an attribution model, a placeholder pending a data room upload, a category with a known gap.
Tip: A confidence level is not a judgment on the analyst who produced the number — it's a statement about the underlying data. Low confidence today, with a clear owner and a path to validate it, is exactly what a good assumption log looks like. Low confidence with no owner and no plan is a red flag.
Data gaps are the explicit list of what's missing rather than silently assumed — DiligenceDesk surfaces them on the Separation Economics overview and in every report so they travel with the numbers instead of getting lost in an appendix.
How Downside / Base / Upside Scenarios Are Derived
Three scenarios, one dataset — no separate downside model to maintain and drift out of sync.
Revenue & Operating Dis-Synergies
Value that quietly disappears after close: lost cross-sell, weaker purchasing scale, and go-to-market disruption that no line item captures on its own.
First 30 Days: Stranded Cost Assessment
A practical sequence for standing up a credible stranded-cost view fast, before deal fatigue sets in.