Revenue Operations & GTM Strategy
I build the operating systems that fix it.
AI can now generate the messaging, enrich the data, and run the plays. It still can't decide which segments are real, what the number actually means, or how to get GTM functions executing from one plan. That's the layer I build — the judgment between strategy and execution that doesn't automate away. I find where the shared logic is broken across B2B revenue orgs, and build the infrastructure that connects it.
Perspective
Every layer of go-to-market is being automated — enrichment, prospect research, message generation, the plays themselves. A capable agent can assemble most of it on demand. The whole category is racing to sell you "context": a context engine, a context graph, a context layer. The word is becoming noise.
Here's what doesn't commoditize. Deciding which 500 accounts out of 10,000 are actually worth pursuing. Knowing what your forecast number means when Sales, Finance, and CS each define it differently. Sequencing a plan the whole revenue org will actually execute against. The tools generate options cheaply now — which makes the judgment about which options are right the scarce resource, not the abundant one.
My work sits at that layer. I'm fluent in the modern AI-GTM stack and clear about where it stops — because the hard part was never the tooling. It was the operating judgment underneath, and that's exactly where I've spent my career.
The problem I solve
Sales, Finance, and CS are each operating from a different version of the business — different ICP, different pipeline criteria, different success metrics. Every tool you add and every hire you make underperforms because the shared logic underneath isn't there.
The result is a forecast nobody fully trusts, a GTM team that's busy but misaligned, and transformations that don't stick.
The pattern is consistent across organizations ranging from $40M to over $1B in revenue: when functions operate from fragmented definitions, execution underperforms regardless of effort. Fix the shared logic first — ICP, pipeline criteria, operating cadence, customer journey — and downstream outcomes improve.
At one company, the ICP meant something different to Sales, CS, Finance, and Product — four functions, four versions of who to pursue. A cross-functional diagnostic built one shared framework from retention data and pipeline analysis. New logo average deal size increased.
At another, a revenue shortfall traced back to the same root cause: no shared definitions for pipeline stages, roles, or opportunity criteria. Building the shared logic got people executing from the same context and pipeline moving in a positive direction.
Different companies. Different symptoms. Same underlying problem.
Career arc
My path from finance into operations was intentional — each role adding know-how the next one required. Across every chapter, the pattern has been the same: when teams lack shared context, execution fragments. My work has been to diagnose where the shared logic is breaking, then build the operating systems that help people execute with clarity.
What I build
Most problems I'm drawn to don't fit neatly into a single function. They sit at the intersection of strategy, data, process, and people — the orchestration layer between what the business decides and what it actually executes. That's where I do my best work, and it's the part that doesn't automate.
Not just a number — a system. Cadences, data models, and dashboard architecture that give the CRO and CFO a single version of truth from pipeline through revenue.
Annual and quarterly cycles that connect capacity, territory, quota, and comp into a coherent plan — not a spreadsheet exercise, but a shared operating commitment.
Finance and Sales don't speak the same language by default. I build the bridges — shared KPIs, joint reviews, and operating cadences that make handoffs work.
Lead-to-renewal, quote-to-cash — the workflows that keep revenue moving cleanly. Built across multiple CRM and GTM stacks; the principles transfer regardless of tooling.
Plans that actually align behavior to strategy — not just quotas on a spreadsheet. Designed and simplified compensation structures across multiple companies and revenue models.
Boards and executives are drowning in data and dashboards — what's scarce is the right insight, framed so it drives a decision. I build the reports and write the narrative that turns analysis into aligned action.
Work with me
Open to senior operating roles where strategy, analytics, process, and operating discipline need a single owner — at a B2B company with real commercial complexity and room to build.
VP · Head · Senior Director — RevOps / GTM / Commercial Operations
Revenue operations leader with 13+ years scaling B2B technology companies by pairing hands-on operational ownership with direct partnership to CROs and sales executives. I lead and coach RevOps teams while owning forecasting, quota and territory planning, CRM governance, deal desk, analytics, and enablement — translating data into action that improves pipeline visibility, forecast accuracy, and deal velocity, and building the board-level reporting that informs decisions and drives growth. MBA, Wharton; BA, Dartmouth.
Prefer the full résumé? Reach out and I'll send it — I'd rather start with a conversation.
Want to go deeper? Explore my full background →
Project-based or fractional work with growth-stage and mid-market B2B companies — GTM strategy, forecasting, segmentation, and operating cadence. See the GTM Foundation Assessment →
Let's talk