Analyses

Most people don't track data, run strategic analyses, or build frameworks, not because they don't want to, but because it's costly, and it takes a skillset built over time to do it well.

I built that skillset across decades and industries. It started in life science commercialization, where I spent two decades reading clinical trial data, real-world evidence, and diagnostic outcomes, then translating that complexity into decisions that mattered: for field sales teams I trained and coached, for physicians and surgeons making adoption choices, for payers and hospital systems evaluating value. Data presented to a surgeon in an Operating Room suite has no margin for ambiguity. You learn to read it precisely, or you lose the room.

The MBA at Boston University's Questrom School of Business added the third layer, of managing performance with data as a formal strategic capability, not just a field skill.

This page is where that discipline shows its work. Below are analyses built on that foundation, across life sciences, AI readiness, and the broader strategic questions that sit underneath both.

Featured Analyses

What 19 Product Launches Taught Me: A Field Guide to Commercial Viability
Nineteen product launches across five therapy sectors — pain management, neuromodulation, autoimmune diagnostics, oral specialty therapy, and biologics — produced a body of field experience that business school frameworks illuminate but cannot replace. This is the anchor post for a five-part series on the analytical frameworks behind life sciences commercialization: segmentation and positioning, pricing strategy, communication architecture, and market access design, applied from inside the commercial process rather than observed from outside it.

The Product Lifecycle Is a Brand Lifecycle
What nineteen product launches across five life sciences sectors reveal about the relationship between product strategy and brand architecture — and why most organizations build brand too late.

The Beast We Built: AI
The governance gap in AI is not a technology problem. It is a leadership problem — and the organizations deploying AI systems fastest are the ones least prepared to govern what those systems actually produce. An analytical examination of AI escalation, the descriptive-diagnostic gap, and why the most consequential decisions about artificial intelligence are being made by the people least equipped to evaluate them.

Healthcare Innovation and Emerging Life Science Hubs
Where life science innovation is concentrating geographically and why it matters for investment, hiring, and partnership decisions across the sector.

Health is the Ultimate Wealth: Florida's Health Systems
A structural look at Florida's hospital and health system infrastructure, sized against the state's population growth and the emerging life sciences hub development.

Methodology & Sources

The analyses above draw on primary data from sources including the U.S. Census Bureau, Bureau of Labor Statistics, Federal Reserve, and U.S. Treasury — the same institutional data underwriters, investors, and strategists rely on, applied with the same rigor regardless of industry.

This page focuses on data-driven analysis; for the broader strategic frameworks behind that work, see Leadership & Journey.