Selling Data Science

Data Science is said to include statisticians, mathematicians, machine learning experts, algorithm experts, visualization ninjas, etc., and while these objective theories may be useful in recognizing necessary skills, selling our ideas is about execution.  Ironically there are plenty of sales theories and guidelines, such as SPIN selling, the iconic ABC scene from boiler room, or my personal favorite from Glengarry Glenross, that tell us what we should be doing, what questions we should be asking, how a sale should progress, and of course how to close, but none of these address the thoughts we may be wrestling with as we navigate conversations.  We don't necessarily mean to complicate things, we just become accustomed to working with other data science types, but we still must reconcile how we communicate with our peers versus people in other walks of life who are often geniuses in their own right.

We love to "Geek Out", we love exploring the root of ideas and discovering what's possible, but now we want to show people what we've discovered, what we've built, and just how useful it is.  Who should we start with?  How do we choose our network?  What events should we attend?  How do we balance business and professional relationships?  Should I continue to wear a suit?  Are flip-flops too casual?  Are startup t-shirts a uniform?  When is it appropriate to talk business?  How can I summarize my latest project?  Is that joke Ok in this context?  What is "lip service"?  What is a "slow no"?  Does being "partnered" on a project eventually lead to paying contracts?  What should I blog about?  How detailed should my proposal be?  What can I offer that has meaning to those around me?  Can we begin with something simple, or do we have to map out a complete long term solution?  Can I get along professionally with this person/team on a long term project?  Can I do everything that's being asked of me or should I pull a team together?  Do I have the proper legal infrastructure in place to form a team?  What is appropriate "in kind" support?  Is it clear what I'm offering?

The one consistent element is people: who would we like to work with and how.  This post kicks off a new series that explores these issues and helps us balance between geeking out and selling the results, between creating and sharing.