Forecasting & reporting
Decompose revenue by behavior so the target reflects what will repeat, rotate, or reset.
The systems behind the descent, shown as working artifacts — not polished claims without the work underneath. Each case study makes the build, the judgment, and the operating signal visible.
The throughline is simple: take ambiguity apart, turn the useful insight into a system, and keep human judgment exactly where it earns its place.
Decompose revenue by behavior so the target reflects what will repeat, rotate, or reset.
Turn brand, pipeline, lifecycle, and content work into repeatable systems a team can run.
Use orchestration, review, and clear decision gates to remove recurring work without flattening judgment.
Design the operating spine before the team exists — then ship the experience that makes it legible.
Why a category’s best-seller this year is rarely its best-seller next year — reading revenue by behavior, not by a straight line.
The full map of a one-person venture — the creator-to-conversion growth engine, the operating spine, and the line where human judgment takes over.
A multi-model AI council, built in n8n, where answers are anonymized, peer-reviewed, ranked, and synthesized into one result.
The actual prompt that let any teammate draft an on-brand newsletter — annotated line by line, with the sends it produced.
A specialty-ingredients rebrand — voice shifted from industrial to personal-care, with a rebuilt newsletter system, sales decks, and formula cards. The concept-to-product story, retold for formulators.
The homepage, as a project — one continuous fall through a generated world: the craft rules that kept a hundred frames coherent, and the engine that ships it.
Chicago-based strategy and operations leader, open to relocation. I turn ambiguous growth priorities into practical systems across GTM, finance, RevOps, marketing operations, and AI automation — especially when a growing organization needs clearer forecasts, decisions, and operating rhythm without more overhead.
My background spans post-acquisition integration in chemical distribution, co-founding a DTC skincare company, and building applied machine-learning systems. The throughline is 0→1 judgment: deciding what to build, what to measure, and when not to scale.
If your team’s growth is outrunning its systems, this is the toolkit I bring. Open to — GTM Strategy & Ops · BizOps / RevOps · AI Operations.