What I Got Wrong About Scale in My Google Years
I spent more than a decade at Google, and for most of that time, I was convinced that reach was the same thing as impact. If a program touched more people, influenced more decisions, or moved a bigger number on a dashboard, it was working. That belief wasn't cynical. It came from a genuine place, shaped by a culture that celebrated performance metrics and by teams I was proud to lead, including one that ranked first globally on those very metrics. But it was incomplete in a way I didn't fully see until I left.
My work at Google centered on civic engagement and elections during a period when digital political advertising was still finding its shape. We were writing rules as we went. And because the stakes felt so high, scale felt like the most honest measure of whether we were doing something meaningful. More reach meant more people informed. More campaigns supported meant more democratic participation. That logic held up well enough inside the walls of a company built on volume. It started to crack the moment I stepped outside them.
The shift came at Dataminr, where I built the AI for Good program from the ground up. My partners there weren't advertisers or campaign managers. They were humanitarian organizations and human rights groups trying to get early warnings into the right hands before a crisis deepened. Scale still mattered, but it wasn't the first question anyone asked. The first question was always: does this reach the person who can actually act on it? A warning that went to a million people who couldn't use it was worth less than a signal that reached the one team that could.
That reframe was uncomfortable. I had spent years optimizing for the broad number. Suddenly I was working in contexts where precision was the whole point, and where a miss wasn't a metric dip but a real failure for real people. It required me to rethink what "performance" actually meant. And it made me look back at my Google years with more nuance than I'd applied at the time.
I'm not saying the work I did at Google was wrong. The civic engagement programs mattered. The industry standards we helped shape around political advertising were genuinely needed. But I think I undervalued the depth dimension: who was being reached, how they were experiencing it, and what happened after the impression. I was fluent in the language of scale and much less fluent in the language of trust. Those are not the same language.
By the time I reached Detroit as Chief Development Officer, that distinction had become central to how I worked. Large-scale investment strategies and public-private partnerships don't succeed on reach alone. They succeed when the people most affected by a neighborhood's trajectory actually have a stake in the outcome. Government and community work forced me to slow down in ways that the tech industry rarely does. Detroit didn't need impressive numbers in a presentation. It needed outcomes that held up after the cameras left.
What I think now is that scale and depth are not opposites, but they pull in different directions if you're not paying attention. The discipline is knowing which one to prioritize at each stage of a given effort, and being honest about the tradeoffs. That's a harder skill to build than optimizing a dashboard. It doesn't show up cleanly in performance reviews. But it's the thing that separates programs that look good from programs that actually hold.
I share this because I think it's easy, especially early in a career defined by measurable wins, to let the metrics become the mission. I did it. The years that followed Google taught me to keep asking the harder question: impact for whom, and in what form? That's the question I carry into every role now, and it's the one I hope to keep putting at the center of the work ahead.