Many parties, no shared goal. I define what counts, then build the engine.
At Atlassian, value moved through a partner ecosystem nobody could put a number on. At HubSpot, five product teams shared 500k users and no agreement on what success meant. Both times the work was the same: figure out how value actually moves, define what the business should count, then build the engine that runs on it. The forecasts, the operating cadence, how teams get evaluated. Defining what counts is the part most people skip, and it's why the rest holds.
- Targeting
- Growth stage teams. Ecosystem, marketplace, or platform complexity. Somewhere the operating structure is still being built.
- Based in
- NYC Metro
- Background
- GTM & Ecosystem Strategy · Product Strategy · Analytics · Data Science
- Focus areas
- Business Planning · XFN Alignment · Team Leadership · Ecosystem Analytics · Partner Attribution
Partner contribution was invisible. The ecosystem was measured like a resale channel even as direct sales and success teams grew around it.
Five product teams shared a 500k+ MAU ecosystem with no shared definition of success. Each optimized for its own activity metrics.
The integration marketplace had no personalization. Every user saw the same generic catalog regardless of use case, stack, or behavior.
HubSpot's integrations had no empirical view of their own coverage. Breadth-vs-depth investment decisions were being made on instinct, and leaders were misaligned.
IBM Software had 20,000 sellers mapped to accounts by gut instinct.
Red Hat was acquired with an assumption that an open-source marketplace would become a major distribution channel. That idea was untested.
Structure from ambiguity
Atlassian's partner business had almost no visibility into itself when I picked it up. Most of the work was not analysis. It was working out what the business actually was, then building the thing that let people run it.
Alignment without authority
None of the five HubSpot product teams reported to me. Neither did the CRO or Partnerships orgs at Atlassian. Getting groups to a shared definition of success when you cannot mandate one is most of the job, and the measurement is how you settle it without it becoming a personality contest.
Output from strong people
I have run teams of four to eight. I give context, align on outcomes, stay close enough to the numbers to be useful, and empower my teams with high ownership, while being a coach for both organizational and technical speedbumps. Underlying all of this is a layer of deep trust driven by purposeful connection.
- 01Clarify the strategy
- 02Identify the system and steps of value creation
- 03Find the decisions the measurement supports
- 04Build attribution, measurement, and operational systems
- 05Drive rigorous, data-backed strategic decisions
My first project at IBM was redefining sales coverage for about 20,000 sellers. The room was deep in the mechanics, which customers belonged in which segment, and nobody had asked what we were actually trying to achieve. Opening with that question changed the path: a clear outcome, a strategy to get there, and implementation plans the data actually supported. I've been chasing that unlock since.
That's the gap I keep finding: organizations build measurement for the layer they started at, then the business changes and the measurement doesn't. At IBM it was go-to-market design and marketplace economics. At HubSpot it was what ecosystem success actually means when five product teams share 500k users. At Atlassian it was what partner contribution looks like when you stop counting partner activity solely on transactions.
Along the way: Chief of Staff to an IBM SVP running a $2B P&L, took Red Hat Marketplace from acquisition thesis to GA product, and built strategic measurement infrastructure inside three separate analytics functions.
The work I'm best at sits at the intersection of measurement, strategy, and executive alignment. Not just building the model: getting the org to optimize for the right thing.
- Roles that fit
- Director or Senior Manager · Strategy & Analytics · GTM Strategy & Operations · Product Operations
- Technical skills
- Python · SQL · Looker · Snowflake · Databricks · Amplitude
- Outside work
- Eagle Scout. Running a Cub Scout pack in Westchester.
- Education
- MBA · Kellogg, Northwestern
- MS + BS · Electrical Engineering, Northwestern
AI I've built.
Building AI tools is part of how I run an analytics function, not a side interest. Some are internal: agents I shipped into Atlassian's partner org to cut time-to-answer and stop pipeline leakage. Others are public experiments that apply the same analytical thinking to strategy problems.
Atlassian Partner Support Bot
Internal chatbot built for Atlassian's partner team. Triages technical and business questions - data availability, trend interpretation, dashboard issues - without human intervention. Reduced time-to-answer on routine questions and freed up strategic analytics capacity.
Deal Registration Agent
Agentic workflow that monitors incoming deal registrations and proactively engages the partner sales team to get registrations reviewed and actioned before expiry. Eliminated patchwork of manual tracking processes that were a consistent source of pipeline leakage.
Arbor
Passion project. Better employee feedback tooling, starting with software developers, a profession with enough structured public data (PRs, reviews, deployment history) to make AI-assisted feedback specific and actionable rather than generic.
WSIAI: What Should I AI?
Individual-level AI strategy tool. Given your company and job title, it maps where your time is going, brainstorms specific buildable agents across six categories, and returns a prioritized playbook: not 'use AI more,' but a concrete agent specification.
Applied AI Strategy Toolkit
A connected set of agents that put a strategist's lens on a business: where customer value breaks down, where margin leaks, why a built agent isn't getting used, and what that agent is actually worth. Each runs on agent.ai.
Let's talk about where your measurement or operating cadence isn't matching how the business actually works.