From Spreadsheets to Domo: A Finance Leader's Honest Take on BI Adoption

When I joined Lacerta Group, the finance and planning function ran on spreadsheets. Not as a stopgap or a legacy holdover — as the intentional reporting layer. Revenue tracking, planning, quoting, sales ops visibility. All of it lived in Excel, shared over a file server, maintained by people who knew which version was current.

This is more common than the BI vendors would like you to believe. It works. Until it doesn’t.

Why We Made the Switch

The honest answer is: we were growing faster than the spreadsheet model could handle. Not faster in revenue alone, but faster in the number of people who needed current information at once. When you have a CEO, a CFO, a VP of Sales, and three regional managers all needing different cuts of the same data on the same day, a single-threaded Excel process starts creating problems.

The specific breaking point was quoting. Our catalog had grown to the point where building a custom quote required someone on the finance team to manually pull product data, apply margin logic, and sanity-check the output before sending. That process took days. Sometimes a week. Sales was losing deals.

That was the forcing function. We needed a self-service quoting capability, and that required a data infrastructure that spreadsheets couldn’t provide.

Why Domo

I looked at the standard options: Power BI, Tableau, Looker. Domo was the right choice for our specific situation for a few reasons:

The data connectors were broad and mostly no-code. We had data coming from multiple sources — our ERP, a CRM, some manual uploads — and getting all of that into a single model without a data engineering team was a real constraint. Domo handled it.

The app-building capability was a secondary differentiator. Domo isn’t just a dashboard tool; it has an SDK for building actual applications on top of the dataset. That’s what made the quoting app possible. We built a form interface where a salesperson could select a product, a customer segment, and a volume tier, and get an approved price with margin detail in real time. That was not a dashboard. That was a workflow application. Domo made it feasible without a software development team.

The licensing model fit a PE-backed mid-market company. We weren’t going to spend $500k on Tableau Server licenses.

What Went Well

The CEO and CFO dashboards came together faster than I expected. Once the data model was stable, building the visualizations was mostly a UX exercise. We went from “I have to ask someone to pull that” to “I can open the app on my phone before a board call” in about three months.

The quoting app cut turnaround from days to under 48 hours. For some simpler quotes, it was same-day. Sales noticed immediately. That visibility created executive buy-in for the broader rollout.

What Didn’t Go Well (and What I’d Do Differently)

Data quality is not a BI problem. The first version of our product master in Domo was a mess because the source ERP data was a mess. Domo faithfully represented the chaos, just in a cleaner interface. We had to go back upstream, clean the product catalog in the ERP, and rebuild. I should have allocated more time to the data audit before the first demo. The demo looked great. The next three months were painful.

The training assumption was wrong. I assumed that a clean interface would be self-explanatory. Most people would figure it out. That was not true. People who had been working from spreadsheets for years had strong mental models of how reporting worked, and a new tool didn’t automatically overwrite those models. We needed more structured onboarding — not “here’s how to use Domo” but “here’s how to answer the questions you’re already asking, using Domo.”

Version control doesn’t go away. With spreadsheets, version control is a nightmare. With Domo, version control looks different but still exists. Who owns which dataset? Who can edit which dashboard? When someone makes a change to a shared dataset, who knows? We had a moment where a dataset that three dashboards depended on was restructured by someone who didn’t realize the downstream impact. The tools to prevent that exist — you just have to use them from the start.

The Honest Bottom Line

BI adoption in a finance function is a change management project with a technology component, not the other way around. The technology decisions matter — pick the wrong platform and you’re fighting your tools for years. But the hard part is always the human side: getting people to trust new reports, changing how questions get asked, rebuilding the muscle memory for where information lives.

If I were doing it again: start with one workflow that’s visibly broken, fix it completely, and let that win sell the rest of the platform. The quoting app was that win for us. Once people saw it work, the dashboard adoption followed.

The spreadsheets didn’t disappear overnight. Some of them probably still exist in someone’s OneDrive. That’s fine. The goal wasn’t to eliminate Excel — it was to make the decisions that matter faster and more reliable. On that measure, it worked.