I really question this "90%" number for "failed" data science teams. While I certainly can see overhype in the space leading to team failure (and I have indeed

I really question this "90%" number for "failed" data science teams. While I certainly can see overhype in the space leading to team failure (and I have indeed seen that), I'm just surprised that the 10% of teams I've been on were so successful by comparison. But one of the nasty things I see happening in the space is that often times really great data science folks, in studying a space, come up with a way to invalidate a lot of the business models. If a major player adopted these, there is a chance of success, but it's also a major risk (as it basically unseats the rest of the business). As such, I think there is a lot of pressure for good data scientists to end up in small teams leading what we'd call 'highly disruptive' businesses. We see this in the finance sector (where it's least likely to succeed) all the time.