Decisions, not dashboards.
I build and own commercial healthcare data products, and develop data teams into product teams that support them. Data analytics, product management, and US healthcare are the operating model; GenAI is the accelerator.
Builds the evidence layer: quality, modeling, interpretation, and measurement that can survive executive scrutiny.
Turns analytics work into customer-facing products, roadmap choices, commercial packaging, and adoption loops.
Applies the work inside provider, payer-adjacent, pharma, and health system operating realities.
Uses agent-assisted execution, evaluation habits, and AI-native workflows to compress learning cycles without losing product judgment.
DPOS is the public model: people, process, product, and platform organized around decision infrastructure.
NeuroBlu, ReviveHealth Market Profiler, HCA Patient Experience, ThinkHaven, InstantDoc, and PM Archetype.
From concept to $9M ARR. Healthcare analytics platforms, market intelligence products, patient experience tools, and AI-native products built for real users.
Develop analysts and data teams into product-minded operators with clearer ownership, stronger briefs, better decision systems, and tighter executive communication.
GenAI workflows, agent-assisted execution, and evaluation habits that stick because they are attached to real product work, not abstract AI demos.
Your dashboard graveyard isn't a data problem.
Data teams drown in insight but starve for decisions. Dashboards don't fix that. Decision infrastructure does.
15 principles that form the foundation of the Data Product Operating System.
The pattern that turns data teams into report factories, and how decision infrastructure breaks the cycle.
Why data products need an operating system, and the four layers that determine whether they ship value.
Ready to ship decisions?
I take on 1-2 advisory clients at a time. If your data team builds dashboards that collect dust while decisions get made in Slack threads, let's talk.
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