Let’s look at the relationship between Data and Story. I’ll be presenting a paper on this subject in December at the Conference on Quantum Storytelling in Las Cruces, NM. It is a complex subject, because it gets at the heart of where meaning resides in organizations and communities, how we share it, and how it moves us.
I’ve been researching the Data-Story relationship for the past four months, and today came across this quote by behavioral scientist Antonio Damasio, from a lecture by him and his wife, Hannah, that I attended in 2009 at the Annenberg School of Communication at USC: “Language covers concepts. Emotion covers feelings.” This is good. This observation describes stories, which are enacted with the “language of emotions.” So what about data? Let’s make a connection between Story and Data by adding one statement to Damasio’s observation–Rule of Threes, you know: Language covers concepts. Emotion covers feelings. Data covers history.
Which gets us to a big question, a question provoked by Dr. David Boje’s theories (language + concepts) about storytelling organizations: How do we feel about history?
Our responses to this question inform our interactions in the present and shape our futures. Improvisation defines these interactions-in-the-present, 0r at least gives us a language for prompting them.
Big Data needs Big Story. Big Story is not your grandfather’s story about that one time that one thing happened. Big Story is your stories and my stories, entangled across networks–then connecting, merging, meshing, unfolding, urfurling and revealing themselves as new stories (or old stories with fresh meaning for a new audience). This process of connecting, merging, meshing, unfolding, unfurling and revealing cannot be scripted. That yields only one, or very few, outcomes. In a networked world, scripting outcomes is highly, highly, highly (can I say it again? yes) highly inefficient. Big Story entails many stories co-created fast and at scale using improvisation. Big Story optimizes decision-making in the present across a nearly-infinite field of possibilities. Big Story consistently improves the likelihood of favorable outcomes in the future, most of which will be unforeseen at the beginning of the co-creation process.
Big Story does not look for meaning in data. That would be like saying the meaning of fire is wood + oxygen x 450 degrees. The meaning of fire can only be discovered in our interactions with it, and in our intentions for its use. The meaning of fire is different for an arsonist than for a cook.
Don’t look for meaning in the data, look for data in the meaning.
Here’s what I mean by this: As a record of its history and a description of its physical properties, data about a fire can probably tell us whether it was used for arson or for cooking–what has been destroyed or what has been created, and how. I do not believe that same data can tell us why, or let me know and understand the people involved.
Data can tell us a lot about What and How. For the Why and the Who that give meaning to data and humanize it, we need stories. (Data and story share the Where.)
Data, in and of itself, is meaningless. More to the point, Big Data contains so much ambiguity that any attempt to find meaning in it can be countered by contradictory information from the same dataset. You say opposites attract. I say birds of a feather flock together. In Twitter’s S-1 filing, I see a bright future for its stock. You look at the same filing and see gloom. Big Data is like a Rorschach test composed of numbers. Only stories created collaboratively, informed by data but not determined by it, can guide us, together, toward a prosperous and peaceful future. One that includes more cooking and less arson.