Most dashboards don’t have a visualization problem. They have a KPI problem.

I’ve reviewed dozens of reporting systems recently and the pattern is consistent:

Metrics are defined differently across sheets

“Revenue” means one thing in finance and another in marketing

KPIs are tracked… but not tied to decisions

Dashboards look clean but don’t answer operational questions

When metric logic isn’t aligned, teams don’t have a data problem.

They have a decision problem.

That’s why I’ve started offering a structured KPI & Revenue Diagnostic Audit — focused on:

• Metric consistency • Reporting logic • Revenue driver alignment • Decision-readiness

If you're building dashboards or scaling reporting systems, this layer matters more than design.

Completely agree. Most dashboards optimize for visuals, not decision velocity. If KPIs aren’t standardized across teams, you’re basically scaling confusion. The real leverage is in metric governance before visualization.

I recently built a mean-variance portfolio optimization model in Excel from scratch — 204 months of return data across 7 large-cap equities including Apple, Microsoft, Procter & Gamble, and Coca-Cola. Using CAPM-derived expected returns, a full 7x7 covariance matrix, and Excel Solver, I identified the optimal portfolio weights to maximize the Sharpe ratio and separately solved for the minimum variance portfolio. The result: a fully documented, professionally formatted financial model with five organized tabs covering price data, monthly returns, statistical analysis, and optimization results. This is the kind of structured, accurate analytical work I bring to every project.

Link to Excel file - https://universitysystemnh-my.sharepoint.com/:x:/r/personal/km1566_usnh_edu/Documents/Portfolio_Optimization_KyranMaher%20r.xlsx?d=w01a1aa9228b04f5891ecfb8524a6d8e1&csf=1&web=1&e=uM8ShI