Paid proof
Analytics Debt Ledger
$12,500 fixed scope
Independent review of one critical forecast, dashboard, metric family, AI-generated output, or board-facing number before it drives an executive decision.
Independent forecast and analytics assurance
Verify the numbers before they reach the board.
Forecast Integrity Partners provides independent forecast and analytics assurance for CFOs, CEOs, PE firms, M&A teams, and lenders making capital-critical decisions.
Proven frameworks test forecasts, dashboards, AI-generated analytics, and deal-critical metrics before leadership relies on them.
No software resale. No vendor kickbacks. No implementation bias.
Where to start
Three executive review paths. One standard: trusted numbers.
Start with the decision risk, not the tool stack.
CFO spend review
Analytics & AI Spend Rationalization Review
$25k to $50k
Review for CFOs, CEOs, and boards that need to cut low-value data, BI, cloud, analytics, vendor, or AI spend without weakening decision quality.
PE / M&A
Analytics QoE / Live-Deal Diligence
$50k to $100k
Forecast and analytics diligence for PE sponsors, M&A teams, private credit lenders, and corporate development leaders relying on management forecasts or deal-critical metrics.
Buyer-forwardable assets
Start with one number.
Before a forecast, dashboard metric, AI-written narrative, or deal-critical figure reaches the board, lender, buyer, or investment committee, test whether it is defensible.
Diagnostic hook
Executive Number Risk Self-Score
A 10-statement self-assessment for one high-stakes number. It scores source traceability, independent build check, stable definition, grain consistency, forecast drivers, overrides, reconciliation, AI traceability, spend-to-value link, and defensibility under questioning.
Product proof
Analytics Debt Ledger Sample
A redacted sample deliverable showing the review output: engagement at a glance, summary judgment, anomaly ledger, detailed findings, scope, and fixed-scope next step.
Proof stack
Forecast discipline at product scale, capital scale, and enterprise-value scale.
The proof page now leads with three real case studies: forecasting built into Tableau, advanced forecast simulations for a $1B+ pharma acquisition, and asset-light international expansion for TV intelligence.
What gets tested
- Source-to-dashboard logic
- Metric definitions and grain mismatches
- Forecast drivers and hidden overrides
- AI summary traceability
- Board, lender, buyer, and investment-committee exposure
Start small
Bring one number, one decision, one deadline, and one concern.
The first step is routing the risk. Do not send confidential data through the public form.