Dispatches from Day Two of the Operational Analytics Conference

Day two of the Operational Analytics Conference featured a star-studded discussion about one of my favorite subjects: creating and maintaining a data-driven culture inside a company and team. Orienting businesses and teams – be it a data team, marketing team or anything in between – around a culture of understanding how to properly use data is absolutely critical. It’s also one of the two core pillars of operational analytics (the modern data stack being the other).

This panel featured:

We had a wide-ranging conversation that covered how companies can become data driven, what happens when they finally get there, and how to maintain that culture as new people, technologies and approaches flow in and out of an organization.

That last piece isn’t easy. Michael brought up an all-too-common problem where data-driven decision making collides with the size and bureaucracy of a big organization.

Michael Stoppelman: One thing I've seen is companies using the data-driven approach to not do something. Analysis paralysis would be the best word for it, I guess. There's this famous Google blog post or story about them trying to pick a color of blue for ads or something. I worked at Google and I saw this in full effect. It was a way of being an organizational blocker on changes. "Well, you need to show us this and this and this and this." In a data-driven organization, it's a way of actually putting up a bureaucratic slowdown on decisions. As a decision-maker in one of those organizations, you have to watch out for folks doing that to prevent things from happening, and not actually having the conversation about whether you want to have it. You end up wasting a lot of engineering time circling around with these decisions, versus just making the hard decision to not do the thing.

Max Mullen: I've seen that, too, Michael. A weaponization of data. My two thoughts on that are, one, that's indicative of a broader problem. Being data-driven doesn't cause that problem, having politics and ego involved in decisions causes that problem. The second is you have to have a certain amount of license for leaders to say, "I've looked at the data. I understand what it says, but here's the flaw,” or “Here is why that decision would be a short-term decision based on this broader context that I have." We're all going to do that, having reviewed the same data and acknowledging that we're ignoring the results of an experiment, for example.

Jeff Ignacio: I've actually seen a different problem where data is brought to the room, but it becomes a credibility exercise where  how folks define key business metrics or key business outcomes differs slightly and causes problems. So for example, the concept of annual recurring revenue versus annual contract value churn. How do you define when the clock starts? Those types of conversations start to spiral out of control. In reality we're all trying to talk about something that's commonly themed across all the executives, but it becomes a credibility exercise and a lot of time gets lost because one little mistake on a slide or some sort of analysis. It sends everyone backwards and spinning.

I loved this panel. It was a fascinating discussion between smart people who have built careers around successfully building data-driven cultures.

Listen to the entire discussion below and be sure to check out the other sessions as well.