The problem is rarely the software. It's the assumptions underneath it.
Companies rarely outgrow Salesforce. They outgrow the operating assumptions someone baked into it three years ago. That gap, between how the company runs now and how its systems were set up to run then, is where forecasts drift and ARR stops tying out. Closing it is the whole job.
Dan Buljan
Lead Operator & FounderI'm a systems builder. For more than 15 years I've gone into growth-stage B2B SaaS companies and rebuilt the revenue and finance machinery underneath them: forecasting, retention accounting, and the reconciliation between Salesforce, billing, and the GL.
I've built the revenue reporting that went into the data room for raises from Series A through C. Those weeks are unforgiving. The questions arrive faster than anyone can answer them, and whatever your systems produce under that pressure is what the round gets judged on.
I've also watched dirty data stall a fundraise, and a compliance audit, more than once. That's why Groundwork runs as direct execution: you work with the person who writes the integrations and the data dictionaries, not a layer of account managers above them.
What 15 years of revenue systems taught me
Bad numbers are usually right answers to questions nobody wrote down.
I've sat in the room while Sales, billing, and Finance each reported a different ARR, and every one of them could defend their number. None of them were wrong. They were answering different questions, and nobody had written down which question the board was asking. I've now seen that same failure at every company I've worked inside, at every stage. It isn't a broken company; it's a structural condition of the stage. That's why every Groundwork engagement starts with definitions and ownership, not with a data cleanup.
The truth about a forecast lives in the lifecycle, not the snapshot.
Amounts change after deals close. Stages get skipped. Close dates slide a quarter at a time. None of that is visible in the current-state view your tools read; it's all in the field history nobody looks at. Reading it, and governing it, is how the forecasting I ran held under ~5% variance for twelve consecutive quarters through a Series A to C run. That wasn't a modeling trick. It was plumbing, inspected weekly, with one owner.
Prevention beats cleanup, every time, at every scale.
A monthly hygiene sprint treats symptoms. A validation rule that makes closed-won-without-a-contract impossible treats the cause. I learned this over nine years at Accruent, where I joined as employee #8 and helped carry the machinery from roughly $5M to $100M+ in ARR through three acquisitions: systems survive scale when the rules are enforced by the system, not by heroics. The same lesson held on an enterprise Salesforce CPQ, CLM, and billing deployment delivered for Google alongside a Big Four integrator. Bigger stakes, same physics.
A number you grade yourself isn't a number a board trusts.
Every tool in the revenue stack reports on its own output. Diligence teams know this, which is why they rebuild everything from source. Groundwork is built independent on purpose: I don't sell the software, I don't own the pipeline, and my only product is whether your CRM, billing, and GL tell one story that survives someone else checking.
The role-by-role history lives on LinkedIn. This page is for what the years taught me.
See where your numbers stand.
The benchmark shows where your metrics and data structures would get flagged in diligence. Twelve questions, five minutes, no email.