In one of my last newsletters, I linked to a Reddit thread, “How does data science work in the consulting space?” and said that if there was enough interest, I’d cover some aspects of data science consulting in the newsletter from time to time. This is the first of those pieces.
Vicki Boykis has some good thoughts on data science consulting. The post points towards the key difference that being a data science consultant forces you to do: quantify the value that your work produces, and then convince others of that value.
While I am seeing a rise in the number of data science consultants out there (which is great!), the reason this point is interesting to me is actually that this skill—quantifying and convincing others of the value of your work—is actually critical for in-house DS’s as well, although its criticality is more hidden. Often, an inability to convince others of value is the underlying reason for your team’s lack of progress, but it’s hard to even realize that’s true because you get that feedback as coded messages. When you’re a consultant, you simply fail to sell the work; the feedback is much more clear.
The very best data science leaders create a vision of data science within an organization and make sure that stakeholders through the business buy in. They then continue to engage in the “selling” process internally with every single project. As in Pardis’ post above, your work, without organizational buy-in, creates no value.