Coaching for better questions
First: take the easy questions off the table.
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When I think about the people in my life who always feel like they’re vibrating at a higher frequency than everyone else—the “smartest,” let’s call them—the thing they all seem to have in common is a deep sense of curiosity about just about everything. Sure, they can share more detail about obscure facts than I’ve ever cared to learn, but their real super power is question-asking.
I’ve been thinking a lot about how to intentionally build that inquisitiveness, both in myself and on teams. Some folks are born with it, but I think, just like anything else, curiosity can be a learned skill.
Data teams in particular benefit from a “we ask really good questions” culture. Data-driven insights are only as good as the stories we tell about them, and to land on a story that’s true, we have to cull through first takes (and seconds, and thirds) with rigor. Without this kind of discipline, we’ll find ourselves making a lot of wrong bets.
So how do we create environments in which the right questions are asked?
Most best practices for building high-performing teams apply here: inducing psychological safety, leaning on the rules of radical candor, assuming best intent. But what’s unique about data teams is that they’re on the hook for not just the accuracy of the analysis, but also of the data itself. Is it clean and reliable? Depending on the size and stage of our organizations, this is often the first question that’s asked of a surprising data story, and this distrust can undercut the real meat of the discussion.
For the sake of depth of conversation, it can be helpful to suspend disbelief about the data set proactively: “we’ll discuss concerns around the data source at the end. For now, let’s assume that the data is correct: what’s the story here?” By simply naming the concern outright and moving that discussion to the end of the conversation, we can make more room for the real stories to surface.
Raman at Rhetoric
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