Brent LaRowe

I’ve spent nearly two decades wrangling data -- cleaning it up, organizing it, and making sure the right people could actually use it. Back when I worked at the UChicago, my job as was to ensure that information flowed smoothly, was reliable, and didn’t get lost in bureaucratic chaos. That experience drilled into me one simple truth: data isn’t useful unless you actually know what to do with it.

So when I decided to figure out whether I could ditch my gas furnace and move my 145-year-old home toward electrification, I did what any data nerd would do—I started collecting numbers. Lots of them. Two years' worth, in fact.

Collecting Data: The Habit That Won’t Die

At UChicago, I wasn’t just keeping records. I was making sure people could find what they needed, that it was accurate, and that it told a clear story. Mismanaged data leads to bad decisions —- whether it’s a student transcript or an energy bill.

That mindset carried over when I started thinking about home heating. I wasn’t going to take someone’s word for it when they said, “Heat pumps don’t work in Chicago.” I wanted proof. I tracked my gas and electricity usage, noted outdoor temperatures, and even logged how often my furnace turned on. I wasn’t just looking for trends—I was looking for the real story behind my energy use.

Raw data is just noise until you structure it properly. I spent years making sure records weren’t just dumped into a system but actually labeled, classified, and usable. Same thing here. Instead of just staring at a pile of kilowatt-hours and therms, I asked:

• How much energy does my house actually need on the coldest days?
• How much heating do I actually need for comfort?
• Can I store cheaper electricity for later use?
• Does my house leak heat faster than I can replace it if I used a heat pump?

By shaping the data into something useful, I got real answers. Spoiler: my furnace is way too big, my house isn’t as inefficient as people assume, and yes, electrification is totally possible.

Governance, Not Just Collection

One of my biggest challenges professionally was making sure data wasn’t just stored —- it had to be useful, accessible, and protected from bad decisions. I had to set rules: What’s essential? What’s noise? Who gets access?

I applied the same logic to my energy project. Just collecting data wasn’t enough —- I needed clear decision-making rules. What percentage of winter days needed backup heating? How much battery storage would cover my needs? I wasn’t just crunching numbers; I was defining a plan that actually made sense for how I live.

People love to argue about home energy. I’ve had more than a few folks confidently tell me that heat pumps won’t work in Chicago, or that solar panels are a waste in winter. But here’s the thing: they’re not working with real data. They’re working with assumptions, outdated experiences, or industry talking points.

I don’t have time for that.

I trust the numbers. My data tells me that electrification isn’t just possible -— it makes financial and practical sense. My furnace is oversized, my heating costs can be optimized, but trying to store cheap electricity for peak-use times isn't (yet) economically responsible. Not when electricity prices in Chicago are as dirt cheap as they are now.

Good data changes the conversation. It cuts through the noise. And when it comes to big decisions—whether at work or at home—I’d rather trust the numbers than the loudest voice in the room.

But how did I get to these conclusions?