15+ years leading data, analytics, and AI teams across multiple industries. The technology is never the hard part. Earning an organization's trust and driving real adoption is the work that matters.
Experience
After 15+ years leading teams across multiple industries, I've learned the hard part isn't the model or the platform. It's the change management, governance, and stakeholder alignment that get people to rely on it.
15+ years leading teams through influence, aligning cross-functional and executive stakeholders around data, analytics, and AI strategy.
Stood up a data, analytics, and AI function from the ground up, from first hire and operating model to trusted, adopted output.
I drive adoption, enablement, and governance. I learned early that success in AI depends on change management and process transformation, not the technology.
Telecom, media, advertising, retail, and CPG. The transformation problem looks the same in every one, and the playbook travels.
I turn business needs into prioritized, well-governed data products, and communicate impact in the language executives use to make decisions.
I define success measures up front and communicate outcomes in the language of dollars and decisions, so leaders can see what data and AI return.
In others' words
What senior leaders, peers, and members of my team have said about working with me.
“Out of everyone on the team, I receive the most unsolicited praise about you.”
“Erv's a change agent. One of the few we have in the entire company. He brings people together. He's built a highly collaborative culture that I believe should be the template for other teams.”
“In my career, I've worked for 6 different companies in multiple roles. In all that time, I've had two really good leaders. You're one of the two.”
My kids started playing baseball recently, and within a week they were obsessed. Then came the questions I couldn't answer:
Who are the good players in the league? How do you know if they're good? What's OPS?
So I built Heat Check, a web app to answer them.
I'm not a software engineer, yet I had a working version running in about 20 minutes. Two ingredients made that possible: a frontier AI model and a trusted data foundation, which I reached through the MLB Stats API. Most people fixate on the first ingredient. The one they overlook matters more. A frontier model can build the app in an afternoon, but if the data underneath can't be trusted, no one will rely on what it tells them.
That foundation is exactly where I've spent much of my career, across telecom, retail, media, CPG, and others. Mining business processes. Defining metrics. Establishing calculations. Gaining alignment across stakeholders, and then making sure the metrics get adopted in practice.
Get in touch
Open to leadership roles in AI transformation, data strategy, and analytics enablement.