I helped take a company public. Here's what nobody tells you about the data side of an IPO. In November 2020, I joined Olo as Sr Director of Data Science and Business Intelligence, the most senior data role.
A few months later, the company went public at a $3.6B valuation. Most people think an IPO is a finance and legal event. It is.
But there's an entire data story happening behind the scenes that nobody talks about. Here's what I learned. Your data has to tell a growth story.
Investors don't care about your dashboards. They care about the trajectory. Every metric you surface during IPO prep has to answer one question: does this company have a predictable, scalable revenue engine?
My job was to build the data strategy that proved it across 80,000 restaurant clients. You will present to the board more than you ever expected. I presented 6 times during IPO preparation.
On data strategy, risk management, and growth opportunities. The board wanted to understand how data products would drive incremental revenue after the IPO, not just support operations. That shift changed how I built the team and the roadmap.
Data products become revenue, not support. We delivered data products that generated $20M in incremental annual revenue through new service offerings and pricing strategy. That's not a cost center.
That's a business unit. When you're going public, the market wants to see that your data capabilities are monetizable, not just operational. You have to build the org while you're running the org.
I built a cross-functional organization spanning data science, engineering, sales, and customer success. 14 direct reports. $7M budget.
All while preparing for the most scrutinized moment in a company's life. There is no "get the team in place first, then execute." You're doing both simultaneously under a microscope. Governance isn't optional.
It's a prerequisite. I led governance using a hybrid COE-Federated model. Centralized data science standards, model risk management, and ethics policies.
Distributed analytics ownership across product and engineering teams. During IPO preparation, investors and auditors want to see that your data practices are mature, documented, and defensible. If your governance is informal, it becomes a risk factor.
The real lesson. Most data leaders build for internal stakeholders. When you're preparing for an IPO, your audience changes overnight.
You're building for analysts, institutional investors, and regulators who will scrutinize every number you produce. That pressure makes you sharper, but only if you were building the right foundation before the IPO process started. If you're a data leader at a company that might go public someday, start building like it's happening now.
The companies that struggle during IPO prep are the ones that treated data as an afterthought until the bankers showed up. I'd be curious to hear from others who've been through this. What surprised you most about going public?