Healthcare Pipeline Management at Scale

Two people covering the entire SE pipeline for a company selling eight product lines into healthcare. The deals ranged from $250K behavioral health proofs-of-concept to $40M health system design partnerships. Each one required deep domain knowledge: different EMR integrations, different payer landscapes, different regulatory constraints, different clinical workflows. Without a system, deals fall through cracks or get shallow technical coverage.

The Deal Management System

I built a structured deal management system spanning 76 prospect directories. Each directory contains a complete deal history: a README with deal summary and current state, meeting notes from every call, open action items, technical requirements, pricing data, and delivery scoping. Every prospect follows the same template structure, which means both a human and an AI can navigate any deal's current state in seconds.

The SE Deal Tracker in Notion provides the executive visibility layer: 99 total deals with stage, health, priority, deal size, win probability, delivery pods, EMR platform, product lines, and SE owner. The schema is centralized in Python to ensure consistency across all automated updates. Fields fall into three categories: Auto (synced from Git at session end), Derived (Claude suggests, human confirms), and Manual (only updated on explicit request).

The Workspace Architecture

Working on 61 deals simultaneously creates a file management problem. I solved it with an ephemeral workspace system built on Git worktrees. When I run /work-on-prospect <name>, the system creates a fresh worktree, checks out the prospect's branch, queries Notion for current deal state, reconciles any drift between Notion and local files, and presents a briefing: deal stage, recent activity, open action items, last meeting date.

When I finish a work session, a session-end hook commits all changes, pushes to the remote branch, creates or updates a PR, syncs updated fields back to Notion, and deletes the local worktree. Zero disk footprint. The worktree is ephemeral; all state persists to the remote branch and Notion. If my laptop stopped working tomorrow, every deal's current state would be recoverable from those two sources within minutes.

This produced 451 pull requests through that workflow alone, one per work session per prospect.

The Verticals and Products

The scope was genuinely broad. Healthcare verticals covered: hospital systems, behavioral health, physical therapy, vision and ophthalmology, dental, ABA therapy, home health, specialty medicine, oncology, and primary care. Products sold across those verticals: SmarterEligibility, SmarterAuthorizations, SmarterReceivables, ConverseAI, SmarterAgents, SmarterPosting, SmarterDenials, SmarterPreBill.

EMR platforms I evaluated integration readiness for: Epic, NextGen, Cerner, eClinicalWorks, Athena, Raintree, Meditech, ModMed, WellSky, Allscripts, iMediware, NextTech, and others. Twelve-plus platforms, each with different API maturity, different EDI capabilities, and different implementation complexity.

The Numbers

61 deals personally managed (62% of company pipeline), $31.8M in pipeline value, $1.95M in closed-won revenue across five deals, 76 prospect directories with complete documentation, 8 product lines across 10+ healthcare verticals. I handled four times the deal volume of the second team member while maintaining quality scores above 80/100.

Salesforce for Executive Reporting

Alongside the custom-built deal management system, I maintained Smarter Technologies' Salesforce CRM as the canonical record of deal flow for the sales organization. While our internal AI-powered system handled the operational depth (meeting notes, technical requirements, action items), Salesforce served as the source of truth for the VP of Sales and CEO when they needed an at-a-glance pipeline view.

I managed deal progression through Salesforce stages, keeping opportunity records current as deals advanced, stalled, or closed. Because the sales team worked across multiple dashboards and reporting views, I built custom Salesforce reports and tailored dashboard components that surfaced the metrics each stakeholder actually cared about: pipeline by product line, close probability distributions, stage velocity, and forecasted bookings by quarter. When the VP of Sales needed a specific cut of the data for a board update, I could build and share a custom Salesforce report in under an hour.

The dual-system approach (Salesforce for executive visibility, custom Git/Notion system for SE operational depth) required careful synchronization. I kept both current so leadership always had confidence in what they were looking at.

Built with: Salesforce, custom reports, pipeline dashboards

Pricing Analysis and RevOps Coverage

Smarter Technologies had a RevOps function on paper, but in practice it was thin. When deals reached the pricing and structuring phase, I stepped in to fill the gap.

I built deal-specific pricing models that incorporated product mix, EMR integration complexity, implementation scope, and customer size. The deal range required different approaches: a $250K behavioral health proof-of-concept has a fundamentally different risk profile than a $15M health system platform deal or a $40M design partnership. I worked directly with the VP of Sales and CEO to pressure-test pricing before it went to the customer, modeling scenarios across different structures: upfront vs. phased payments, multi-year discount curves, and what the customer-side economics looked like for each option.

When pricing negotiations got contentious, I could show the analytical work behind our numbers: what components drove the price, what could be removed to hit a lower figure without breaking the economics, and how the long-term value calculation looked for both sides. This was a natural extension of the ICP and pipeline analytics I was already running. The person with the deepest understanding of each deal's technical scope and win probability was also the right person to build the pricing model for it.

The boundary between SE and RevOps was functionally blurred at Smarter Technologies. I ran both functions for most of the time I was there.

Tech Stack

Notion (deal tracker databases, health indicators, status fields), Salesforce (CRM, executive reporting, deal flow), Git (version-controlled deal state and history), Python (schema validation, deal tracker audit scripts, pricing scenario models), Claude Code (automated field updates and briefing generation)