Done. I've created a complete forecast accuracy assessment for the CFO with three deliverables:

## Summary of Findings

**The outlooks are worth trusting.** All FY2025 forecast versions came within 3.2% of actual results—well above industry standards:

- **9+3 version** (99.98% accurate): Essentially perfect with only $2.76K error on $11.2M revenue
- **6+6 version** (99.26% accurate): Very good mid-year reforecast, only 1.4% off on revenue
- **3+9 version** (98.94% accurate): Solid early reforecast with limited actual data
- **Budget** (98.38% accurate): Conservative on revenue (+3.2%) but nearly perfect on operating expenses (off by $649)

**Key insight:** Operating expenses are predictable (all versions within 0.55% of actual), while revenue has more variance but follows expected patterns as actual data is incorporated.

## Deliverables Created

1. **EXECUTIVE_BRIEFING.txt** — One-page summary with answer upfront, key metrics, and FY2026 recommendations
2. **FORECAST_ACCURACY_REPORT.md** — Detailed 6-section analysis including findings, accuracy rankings, and strategic recommendations
3. **forecast_accuracy_dashboard.html** — Interactive charts and data tables (open in a browser to view)
4. **analyze_forecast.py** — Reproducible analysis script for validation

All files are in `/tmp/spb-forecast-accuracy-fy25-v2-claude-72_00qz2/` ready to share with leadership.