Summary
A growing SaaS company had a revenue engine held together by spreadsheets, disconnected tools, and tribal knowledge. As the team scaled, this became a hard limit on growth. I led the redesign of the full revenue operations stack—tools, processes, and reporting—turning a fragile patchwork into a system the team could depend on.
Headline result: Forecast accuracy went from 58% to 87%. Weekly revenue reporting that once took a full day now runs in under two hours.
Context
The company had grown quickly from its first 20 customers to over 200, but the revenue operations infrastructure hadn’t kept pace. Sales was using one CRM, customer success was in spreadsheets, and leadership was reconciling conflicting numbers every week before the Monday all-hands.
The company was heading into a Series B fundraise and needed a clean, credible revenue picture—fast.
The Problem
Three distinct issues compounded each other:
- No single source of truth. Sales, CS, and Finance each had their own version of ARR, churn, and expansion data. Alignment required manual reconciliation every cycle.
- Manual, error-prone reporting. The revenue report was built by hand each week, taking 6–8 hours of a senior analyst’s time.
- No early warning system. Churn signals existed in CS notes but weren’t visible to leadership until a renewal was already at risk.
The underlying cause wasn’t just tooling—it was that nobody owned the full revenue operations function. Each team had optimized locally.
My Role
I was brought in as program lead to define the scope, build the business case, and own execution end-to-end. This included:
- Running the current-state audit across Sales, CS, and Finance
- Facilitating alignment between three teams with conflicting priorities
- Owning tool selection (evaluated 4 platforms, built the comparison framework)
- Managing a 6-person cross-functional implementation team
- Defining success metrics and running the 90-day post-launch review
I did not write code. I made decisions and removed obstacles.
Approach & Key Decisions
Discovery first, solutions second. Before touching any tools, I spent three weeks mapping how data actually flowed (vs. how people thought it flowed). The map revealed that the core problem wasn’t the CRM—it was that two key handoffs between Sales and CS had no defined owner or format. We fixed the process before we fixed the technology.
Consolidate, don’t rebuild. The temptation was to implement a new platform across all functions. I pushed back. We kept the existing CRM for Sales (adoption was high, disruption cost was real) and built a lightweight integration layer to sync CS data into a single reporting warehouse. Total implementation time: 6 weeks instead of the 6 months a full replacement would have required.
Start with the report, work backwards. I had the leadership team define the exact revenue report they wanted to see at month-end. We then reverse-engineered the data model from that output. This prevented scope creep and gave the team a concrete finish line.
Change management as a deliverable. We built a 4-week enablement program alongside the technical rollout. Every manager who touched the new system got a 30-minute onboarding session and a one-page reference guide. Adoption at week 4 was 94%.
Outcome & Results
| Metric | Before | After |
|---|---|---|
| Weekly report build time | 6–8 hours | <2 hours |
| Forecast accuracy | 58% | 87% |
| Churn signal lead time | 0 days (reactive) | 21 days (proactive) |
| Cross-team data disputes | ~4/week | <1/month |
The project also unblocked the Series B process. Investors reviewing the data room for the first time noted the revenue reporting was “unusually clean” for a company at this stage.
Key Lessons
The org problem is usually upstream of the tool problem. We could have spent months evaluating platforms and it wouldn’t have mattered—the handoff process between Sales and CS was the real blocker.
Boring beats clever. The final solution was not technically impressive. It was SQL queries, a well-structured data model, and a dashboard anyone could read. That’s what got adopted.
Define done before you start. Agreeing on the target revenue report at week one saved us from scope creep that would have pushed the timeline out by months.