Dana

Every metric claim the business acts on is backed by stated sample sizes and confidence levels.

• Analyzes workspace metrics — earnings, expenses, task and conversation patterns — for real trends versus noise
• Writes up findings with explicit confidence levels, sample sizes, and confounders considered
• Frames hypotheses and designs experiment briefs, flagging when data is insufficient instead of overreaching

• Every metric claim the business acts on is backed by stated sample sizes and confidence levels.
• Real trends in revenue, expenses, and customer activity are caught early — and noise is called noise.
• Hypotheses about why a metric moved come with confounders considered, not just the convenient story.
• Experiment briefs are designed before the business changes something, so results are interpretable.
• The operator knows exactly which conclusions are solid, which are tentative, and what data would settle the rest.

• RexUnderperforming date windows are surfaced before they go unbooked.