Every add-on brings its own systems. I pull them into one view leadership can trust, updated automatically, without hiring a data team.
What reporting tends to look like after the second or third acquisition
Each add-on came with its own system and its own chart of accounts, and none of them line up.
The monthly P&L and board package get rebuilt in spreadsheets every month, usually by the same one or two people.
Finance and operations bring different revenue figures to the same meeting and spend it arguing over whose are right.
Lender and sponsor reporting takes days your team doesn't have, right when the next deal needs attention.
Reporting that keeps up as you add businesses
Finance and operating data from every business in one place: P&L, margin by plant or branch, sales and backlog. Your controller signs off on the definitions, so the numbers match the books.
The monthly package, built from the same data every month instead of rebuilt by hand in spreadsheets.
A repeatable process for bringing each new acquisition into the same reporting, so the next deal doesn't start from scratch.
The usual instinct is to integrate every ERP before anyone agrees on what the numbers should be. I start with the 10 numbers leadership needs, build one trusted version of them, then bring in the rest.
From my work at InfluxData and the Boyd Group
There was no warehouse, and every team kept its own spreadsheets, so revenue, usage and marketing numbers never lined up. I built the first warehouse in Snowflake, brought in Salesforce, product usage and billing, and Marketo, then built Domo dashboards for leadership, sales, marketing and product. My analysis of the usage data led leadership to rework onboarding.
Staff used an AI assistant to answer questions from SOPs and training documents, but it was missing features and nobody could tell when it gave a bad answer. I led the three-person team that took it over, rebuilt the experience, and added answer ratings that sent bad answers straight to the content teams. Then I ran the rollout company-wide, including to the shops from a ~250-location acquisition.
From a first conversation to numbers you can trust
We talk through how your numbers come together today and what's at stake. If there's a fit, I follow up with a free 60-minute health check and a one-page summary of what I'd fix first.
A flat-fee review that ends in a written plan and a fixed price for the build. The fee is credited toward the build if you go ahead.
Starts once I have system access. Everything is documented, and I train your team so they can own it.
I was at the Boyd Group when it absorbed a ~250-shop acquisition, so I know what the months after a deal look like.
I've built these pipelines before, so your budget doesn't go to me learning the basics. The goal is first numbers within 4–6 weeks of system access.
A senior data engineer costs $160K+ a year and takes months to hire. A fixed-scope build costs less and is done in weeks.
I scope it, build it and document it myself, so your team or a future hire can run it without me.
Two ways to work together
Fixed scope and fixed price, set during the diagnostic. Every engagement starts here.
Keeping your reporting running as the business changes, plus new add-ons and reports as they come up. Billed monthly.
Book a 30-minute intro call. Tell me how your numbers come together today, and I'll tell you honestly whether I can help.
Book a 30-Minute Call