Storytelling: The Power to Influence in Data Science
By Tyler Byers, Comverge, Inc.
Humans are story-telling animals. We love a good story. Stories, whether in the form of movies, epics, songs, or myths: they capture us, they move us, they bind together generations, get us in touch with deeper messages. Everyone knows how to tell stories, at least a little bit. But, certainly some of us seem to have more storytelling talent than others. That group of five or six friends you hung out with in college: there was probably one person in that group that everyone loved to listen to. They could tell stories for hours on end – funny stories, stories that made you think, stories that made you cry, stories that changed your life. This person, they didn’t necessarily know more about the world than you. But they knew how to craft their message in an interesting manner, and likely had an outsized influence on you and your circle of friends.
As Data Scientists, we need to be able to influence. We have data and insights that can shape the direction of a business. But all our insights are for naught if we can’t convince the leaders in our business to act on our insights. Our Data Science peers might be interested in the details of our heroic data wrangling, or seeing how many models we ensembled, or how many features we engineered. Leaders of our business? Unless our work can save or generate dollars, they see nothing more than perhaps a grown-up version of a science fair project. That’s right, I’m comparing your sophisticated models that took you three months to build to a fifth-grader’s papier mâché volcano . Interesting and fun, but eventually just clutter in your bedroom that you throw out with the garbage. Hopefully you had fun and learned something, even if you didn’t win that ribbon!
Not my volcano, but I made one like it sometime around fifth grade.
So, as Data Scientists, how can we influence? How can we convince our company leadership to act our insights? I struggled with this when I began my current job. The five-minute morning standup meeting and occasional ggplot visualizations dropped into Slack chat weren’t enough. I was doing (what I thought was) cool work, but it wasn’t affecting the direction of our product. So I found my voice. I began telling my data’s stories, and writing the stories down. Working hard on visualizations. Thinking about my audience’s needs. Asking lots of questions – finding out what my business needs were, not just what I found interesting in the data. I began focusing on how I wascommunicating my insights. And things began to change. It’s still (and always will be) a work in progress, but I am having increasing influence as my communication and storytelling improve.
How I Communicate my Results
It starts with the blog. Last September, I spent a couple days figuring out how to start a Jekyll -driven blog on our company’s GitHub Enterprise install. At first I was worried that my time setting up the blog would be wasted – these were a few days when I wasn’t doing data work, after all. But this has been one of my best decisions I have made. I blog about two to three times a month, at various “stopping points” in whatever project I’m working on. I love the blog because the words are mine, and I don’t have to worry about sounding too formal. I can easily cross-reference previous blog posts. Writing helps me organize my thoughts, helps me record additional questions, and provides a repository of ready visualizations if I need to have a presentation ready quickly. I forget what I worked on just two months ago. I forget what ideas I had two months ago. If I go to my blog, I get that refresher much better than I would had I left the results in an R Markdown file in a random directory on GitHub. And I can easily share my blog links with company leadership.
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