Today’s blog post will be a little on the light side as I explore the various things that come up in my experience working as a data scientist.
I’d like to consider myself to have a fairly solid understanding of statistics*I would think it's accurate to say that I may be slightly above average in statistical understanding compared to the rest of the population.. A very large part of my work can be classified as stakeholder management - and this means interacting with other people who may not have a strong statistical foundation as I have. I’m not very good at it in the sense that often people think I am hostile when in fact all I am doing is questioning assumptions*I get the feeling people don't like it but you can't get around questioning of assumptions..
Since the early days of my work, there’s been a feeling that I’ve not been able to put to words when I dealt with stakeholders. I think I finally have the words to express said feelings. Specifically it was the transference of tacit knowledge that bugged me quite a bit.
Consider an example where the stakeholder is someone who’s been experienced in the field for quite sometime. They don’t necessarily have the statistical know-how when it comes to dealing with data, much less the rigour that comes with statistical thinking. More often than not, decisions are driven by gut-feel based on what the data tells them. I call these sorts of processes data-inspired (as opposed to being data-driven decision making).
These gut-feel about data can be correct or wrong. And the stakeholders learn from it, becoming experienced knowledge. Or what economists call tacit knowledge.
The bulk of the work is of course transitioning an organization from being data-inspired to becoming actually data-driven.