In this episode of the podcast, Mike and Doug talk about being data-driven versus being goal driven.
[Heads up: if you'd like to skip past a discussion about GDPR, begin at the 12 minute mark]
At the beginning of this discussion about "being data-driven". Mike says, getting emails that aren't targeted is a symptom of a lack of good data sets. There's data-driven aspects to some emails when thinking, "Why are we doing this and is this the smart thing to do?" But then there's data sets, where you'll ask, "Is this clean, up-to-date, segmented, etc.?" This isn’t data-driven, this is data-based.
What does it mean to Doug to be data-driven? Doug said, watch baseball. The most obvious place you'll see someone being data driven is watching how baseball players field. Doug refers to these numbers:
MLB Shifts by Season
The use of data and the use of advanced analytics is visual. You use heatmaps, locations and charts, and then you start taking action in relation to what the data is telling you...even if the data is telling you something that may be difficult to believe. Being data-driven is a lot like thinking about science. If you like to follow advanced thinking about problems, be sure to check out Richard Feynman's Twitter account here.
Data-driven is also about being probabilistic. Goal driven is focusing on where you currently are and being metric driven, while being data driven is what's causing that result. Doug says, people measure efforts, activities and results and refers to this graphic:
As Doug closes, he reminds us...If you want to be happy, be metric driven. If you want to scale a business, be data driven.