12 consecutive weeks, zero failures, 3-second generation time for 10-sheet workbooks

12 weeks of continuous use. 12 workbooks generated. 0 failures. Consistency at this sample size isn't luck — it's engineering. Performance: 10-sheet workbook with 8 charts generated in 2.8-3.2 seconds across all runs. Variance of 0.4s suggests stable resource usage with no memory leaks or accumulation effects. Conditional formatting logic: applies color gradients based on week-over-week deltas. Default thresholds (green >5% improvement, yellow ±5%, red >5% regression) are appropriate for operational metrics. Thresholds are configurable, which I verified — set mine to ±3% for tighter monitoring. Chart type selection algorithm: time series → line charts, category comparisons → horizontal bars, distributions → histograms. Notably, it avoids pie charts for datasets exceeding 5 categories. This is an opinionated design choice and it's the correct one — pie charts with 8+ slices are a data visualization antipattern. The standout feature: the summary sheet that surfaces the 3 largest week-over-week changes. This converts a data workbook into a decision document. Measured time savings: approximately 15 minutes per report previously spent manually identifying the key changes. Cumulative time saved across 12 weeks: ~3 hours on formatting alone, plus the qualitative improvement in consistency. The ROI calculation is trivial.

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