Perfect! I've created a comprehensive analysis of your FY2025 reforecasts. Here's what I found:

## Summary

**Your reforecasts were exceptionally accurate:**
- **9+3 reforecast** (after 9 months): **0.12% MAPE** — essentially perfect
- **6+6 reforecast** (after 6 months): **0.91% MAPE** — excellent
- **3+9 reforecast** (after 3 months): **1.92% MAPE** — very good

The accuracy improved **16x** as the year progressed and you incorporated actual results.

## Key Findings

1. **Operating expenses were consistently more predictable** — even the early 3+9 forecast hit OpEx within 1.32%, vs 2.51% for revenue

2. **The summer dip was the biggest surprise** — September revenue was overforecast by 15% in the 6+6 (mid-year) reforecast, suggesting you didn't fully anticipate the seasonal slowdown in your H1 planning

3. **Full-year precision was remarkable** — the 9+3 forecast nailed it:
   - Revenue: $11.24B (off by $2,800 = 0.0%)
   - OpEx: $2.53B (off by $631 = 0.0%)

4. **Q4 remained tight even with forecast data** — even the later portions of the year that relied entirely on forward-looking predictions hit within 0.47-1.6%

## Deliverables

I've created three files:
- **FY2025_REFORECAST_ANALYSIS.md** — Detailed written report with month-by-month breakdown and recommendations
- **forecast_visualization.html** — Interactive dashboard with accuracy charts and trend analysis
- **analyze_forecasts.py** — The analysis script if you need to re-run or modify calculations

The main recommendation: investigate seasonal demand patterns for next year. Your excellent cost control makes OpEx predictions reliable, but capturing summer/Q3 demand variations would improve early-year revenue forecasts significantly.