Teaming with Data

Teaming with Data

Oh—excuse me. I didn’t see you there. Why yes, I am watching another episode of Star Trek. And yes, I am writing on Beehiiv, not Substack, in another likely-to-fail newsletter.

What’s it about, you ask? Well . . . ::leans in from armchair:: . . . I have a sort of working theory that there is a gap in research about data analytics teams. I find that articles and books rely too much on interviews or anecdotes on the subject. I have yet to ever see a true study of data on data analytics teams.

Even if that market is already set, I feel pretty strongly that the writing that does exist about data teams lacks, well, data. We are literally teeming with data on how analytics teams operate. Why does most management advice on the subject rely on stories of teams that don’t do analytics, data science or engineering? How do the best quotes come from military and sports references? Why do I have to listen to an entire audio-book on management only to hear a single anecdote that I can actually relate to as an analyst?

What I find lacking on the high-quality, fully-vetted source that is the world wide web, however, is one place for discussion on how to coordinate an analytics team in a dynamic business context. Some good attempts have been made, for sure, but I don’t know of an actual analysis on the best data teams in history.

So with this newsletter, I want to explore the best data teams in history - how did they work? What made them tick? What lessons can we draw from their mistakes? Sure, we might learn a little about becoming a better analyst or manager, but it’s more about solving business problems with data and organizational design.

Meanwhile, you can find me piddling away at the keyboard here on my living room couch after my toddler has gone to bed, squandering a perfectly good hour by writing about my little contribution to the tomb of technology and leadership.

Now back to Star Trek—Engage.