Once Upon a Time

It’s that time of year when holiday parties start happening, and you get a chance to reconnect with family and friends that maybe you haven’t seen in a while. Inevitably at these types of get-togethers, people will ask “what do you do?” When I talk to them about data management or analytics management, it’s clear that, for many of them, it’s something that they don’t think about a great deal, and at first, it’s a challenging profession to really grasp.

In explaining my work, I will often fall back on a theme that I’ve used for a long time now. I’m sure that I’m not the only one who describes things this way (in fact, I know I’m not), but for me it’s one of the best ways to describe the type of work that I enjoy and do.

Data tells a story, is usually how it begins.

Data tells a story, about how a business operates. Where it makes money and where it spends money. Data tells a story about who their customers are, where they live, what they buy and how often they come back. Data tells a story about what factors affect how successful the business is - where they advertise, what they advertise, where they’re located, what their hours are.

Data professionals - whether it’s an entry clerk, a data engineer, a data analyst or scientist, or any of myriad new descriptions that evolve each day - work to take the rough outline of the story, the bits and pieces of dialogue, the abandoned plotlines, and weave them all into a cohesive plot, a compelling tale.

We do this because it makes the story more interesting. When Disney released Cinderella, it wasn’t just a story about a girl who found a shoe that fit really well. The girl had two evil step sisters. She toiled all day, every day, cleaning a massive home. She had never had a day of fun in her whole life. The shoe wasn’t just a shoe, it was a glass slipper. It was carried by a handsome prince. It promised a life of luxury and freedom from her awful situation. By adding details to the story, drawing a picture that is impossible to ignore, we’re drawn into the tale and care about the characters. We start thinking, getting ahead of the story, imagining what we would do in those situations, or what we might suggest Cinderella do, for example.

Similarly, all of this data “stuff” that people in this industry do, it adds color, vibrancy, life, to the outline that the raw data gives us. We know that 50% of our customers are between 22 and 38. We know that our customers are more likely to be women than men. We can see how the popularity of products in our stores changes over time, we can watch the dance that the market share curves do leading up to Christmas. We can establish hypotheses about why our customers behave the way they do, and we can make predictions about what they’ll do next.

In essence, data work is storytelling. And to be a good storyteller, you need to be fluent in the language.