I’ve been at 37signals for a couple of months now, and I thought I’d introduce myself and share the answers to a few questions I’ve been asked. I’m our “business analyst”, “data guy” or “stats guy”, but those all leave some explanation lacking of who I am and what I do.
Who are you?
I’m a mechanical engineer by training, but I spent the last couple of years working at McKinsey & Company, a consulting firm. I did a range of different things, but spent most of my time focusing on understanding and predicting individuals’ behavior as it relates to the healthcare system – how people use physicians, hospitals, and their health insurance policy. I live and work just outside of Pittsburgh, PA.
What would you say you do here?
I tend to think that there are three things that I’m trying to do.
- Look at data to try to improve our products- understanding how people interact with and use our products helps us make better decisions about how to improve them. Sometimes this is about new features; other times, it’s about the smaller details – where does a pagination break make sense based on how many projects people have?
We’re planning to share some specific examples of how we’re using data to inform design decisions over the next few months.
- Use data to help grow – Too much of using data to “help businesses grow” is about predicting (guessing) revenue or profit in five years. This is kind of fun intellectually (and there are cleverly named tools like “Crystal Ball” to do this), but it’s less useful than finding real things that we can do today or in the near future that will meaningfully impact the business. This means focusing on why people cancel, how they interact with signup pages, etc.
- Answer those “I wonder” questions- one of my favorite parts of working at 37signals is watching products develop every day in Campfire and on Basecamp. While doing that, people occasionally start a sentence with “I wonder…”. I get to move from wondering to knowing, and that’s loads of fun to do.
How do you do what you do?
There’s nothing magical here – most of the challenge is just about knowing the right questions to ask and understanding the relationships between data. The actual tools matter a lot less.
We have a few reporting tools that we’ve built, and use a few commercial tools (Google Analytics, Clicky), but most analysis gets done from raw data. I do virtually all of my work within a statistical programming language called R (with a couple of custom functions to interface to our databases and APIs for Clicky, etc.) and with simple unix tools like awk/sed. This combination is incredibly simple, powerful, and adaptable, and R has a great community behind it. I use a couple of different tools to produce graphics (mostly ggplot2 in R and OmniGraphSketcher), and I’m experimenting with narrated screencasts, etc. to share results as well. Of course, my trusty HP-12C never leaves my desk.
Have any other questions? I’ll try to answer any below or in a future post or podcast.