Operator inside a team
Axenya · B2B, Corporate health benefits
From a five-day forecast ritual to real time
Axenya, a B2B corporate health broker with 81 people, ran forecast by exporting the entire pipeline to Excel and recalculating it cell by cell, by hand. Four to five days of work, repeated every two weeks, for a pipeline in the hundreds of millions in ARR. Nobody on the product team had ever looked at it.
My roleRevenue Operations Analyst, four months. I translated revenue leadership’s strategy into a working system, then built that system myself: architecture, the dashboards, the rules, the rollout.
- Shipped a dashboard platform from zero: 8 panels covering CRO, Forecast, Board, AE, BDR, Last 48h, Delta, and Coverage views, each chart auditable back to the exact CRM fields behind it.
- Built a semantic catalog as the single source of truth for every business rule, with documentation generated straight from it. Building it surfaced two probability rules running side by side unnoticed: the same stage was worth 18% on one screen and 33% on another.
- Turned a meeting into a written four-step forecast ritual: per-rep prework, named data-hygiene follow-up, post-meeting to-dos, and a consolidated report showing the delta against the previous cycle.
- Rebuilt the CRM’s business-rule layer as fields and automations, not verbal agreements: ARR modeling by compensation type, automatic company-size classification, a canonical close-date definition, and automated inactivity handling.
- Shipped a daily Slack pipeline report and automated field-hygiene nudges per rep, each with a direct link to the record.
- Remapped handoffs across Sales, Quoting, and Implementation: correlated fields, shared quote files, and stalled-quote alerts, surfacing roughly 60 stuck deals during rollout, some tied to reps who had already left.
The infrastructure never went down, not once in three months in production. Every hour of rework came from a business premise that changed mid-cycle: does a POC count as revenue, is stage four active pipeline. The machine was never the bottleneck. The person deciding was. I found the same pattern in adoption: reps were not filling fields because the screen was full of information that mattered to RevOps and to nobody selling. There were fields that mattered to me and to nobody else. So I stopped asking for them upfront.