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About

The Story

How I went from "we have all the data" to "we have no idea what to decide."

The Origin

Every data team I've worked with has the same problem.

Smart people. Good tools. No decisions.

At NeuroBlu, we built a healthcare data+ analytics platform from scratch to $9M ARR for neuropsych. Regulatory ready. 36 million patient records. Partnerships with every major pharma company you've heard of.

And still, the hardest meetings weren't about data quality or model accuracy. They were about deciding what to build next.

The Pattern

  • Dashboards nobody looks at
  • Automations that accelerate the wrong work
  • "Data-driven" cultures that can't make a single decision without three more analyses

The problem isn't data. The problem is decision infrastructure.

The Insight

"Most teams are insight-rich and decision-poor. They have 47 dashboards and zero clarity on what to build next."

Here's what I learned shipping real products: Tools encode clarity. They cannot create it.

You can automate a workflow that shouldn't exist. You can build a dashboard that answers the wrong question. You can train a model on data that doesn't matter.

The upstream work, deciding what to build, what success looks like, and how you'll know if you're wrong, that's what actually moves the needle.

That's decision infrastructure.

What I Do Now

I help small data teams build the systems they're missing:

Decision logs — Not meeting notes. Structured records of what was decided, why, and how you'll measure if it worked.

Context graphs — The relationships between people, problems, and priorities that determine what gets built.

Outcome loops — Mechanisms for learning whether your decisions were right and feeding that back into the next one.

This isn't consulting theater. It's the stuff I wish someone had taught me before I spent three years building features nobody used.

Background

Professional:

  • Director of Product, NeuroBlu Analytics (Holmusk)
  • 10+ years data analytics + consulting professional
  • Previously: Naval officer, consulting

Education:

  • Kellogg School of Management, MBA
  • Vanderbilt University

Service:

  • U.S. Navy veteran

What I Actually Do:
Write code. Ship products. Train teams. Question assumptions.

Personal

I live in Charleston, SC with my wife Kristyn. We moved from New York City to be closer to family and friends.

When I'm not thinking about data products, I'm probably:

  • Reading something contrarian
  • Overcomplicating a simple home project
  • Riding my bakfiets (ecargo bike)
  • Building something with Claude Code that may or may not be useful

Let's Talk

If your data team is drowning in dashboards but starving for decisions, I can help.

Email me or fill out the form.

Or start with the newsletter — it's free.