Dave is a product and data coach helping empower data culture in organizations. He’s based in Minneapolis, MN.


"There is this constant gap, constant divide between the business and technology.  And people like [Harvard Business Review] say, 'we need these translators, we need this’. No, we need the business to give a shit.  This is important, you can’t sustain businesses without this, so let’s solve this problem."

Dave runs the Twin Cities Data Fluency Group in Minneapolis. I found him on Meetup, hunted him down on LinkedIn and introduced myself. You get the impression from Dave that he would very generously stop what he’s doing and chat with anybody, anytime, about data. The mail carrier. Your cousin Brian. Your classmate Louise.

Dave spends his days helping organizations do better with data. He thinks about things holistically, recognizing these changes are hard. They need to be top-down and bottom-up. There needs to be a supportive and capable culture to enable this progress. Part of the work is assessing how ready an organization is, if the timing is right (it isn’t always), and what constitutes the best approach for them on this journey. It’s “almost like being a therapist”, he notes, understanding an organization’s history, pain points, and what might be the best early ROI to get the ball rolling wisely, incrementally. What emerges from our chat feels like a data corollary to Tolstoy’s Anna Karenina principle - All successful data cultures are alike; each dysfunctional data culture is dysfunctional in its own way.

This kind of holistic view makes more sense to me as Dave describes his background. A BS in Chemistry, MS in Information Assurance during the early days of the discipline, a u-turn 2 years into a PhD and a JD. After coming to the conclusion that he “hated” being an IP attorney, and that litigators “either were burnt out or were addicts”, he switched over to product management. It just so happens most of those products had an analytic bend - risk models, pricing models, etc. Now he helps organizations find their voice, informed by Daniel Kahneman‘s two thought systems, a path to “data empowerment”, if you will:

"How do you empower them? You let them feel comfortable asking questions, thinking creatively around data, communicating with data, but not leading with data, communicating with stories, because being a good story-teller is the first part...System 1 is powerful, folks, and if you try to dismiss it and say ‘well we’ve got the better argument, listen to us’, guess what? They’re not going to get to your argument, they’re not going to get to your data.”

Stories are nice, but the devil is in the details, and banal operational choices like reporting structure and team arrangement make a big difference. On this, Dave looks towards the field of User Experience, and how it’s become embedded within many organizations, as a model that data work can look towards.

"I understand why it’s easy to say, let’s put [data scientists] over there…You’ve got hard core nerdy R&D data scientists, yeah, that group you might treat differently, think of differently, but that’s a really small group. That’s the outlier. Then every one of those other [data-focused] groups, how do you embed them? [There’s an inclination] to say we’ve got to sit them together otherwise we’re afraid they’re going to get ‘influenced’ too highly by the business...but I think it’s more valuable that they’re in the business.”

We know there’s no perfect, one-sized fits all approach to help organizations move their way up the data ladder. Every place has it’s own personalities, gripes, trauma, champions, inertia, weaknesses, and strengths. Tolstoy just might have been onto something.


Storytelling with Data

Behavioral Grooves; Podcast

Data Literacy Project


Beyond the Data

Data Able; Podcast