Numbers, on their own, represent quantity, and do not guarantee quality. 100 can be a perfect score on a test, an average IQ, or a bad round of golf. What guarantees quality is the story that provides context for the data. Data and stories are co-constituted. One cannot, does not, exist meaningfully without the other.
The purpose stories serve, have always served, is to put data (i.e. recorded history) into a useful context and help us make smart bets on the future. Stories make sense of information. They help us choose what parts of our history are most relevant to our present-day decisions and are most likely to shape our desired futures.
I wince when I hear leaders or their companies boast that they make ‘data-driven decisions.’ If data is driving your decisions and you don’t weight storytelling equally–if you’re not making [data + story]-driven decisions–you’re rowing with one oar in the water. We know what that means. You’re going to move in circles. When you rely on data alone to make decisions, good, mediocre and bad options for taking action can be presented with equal merit, and leave an audience wanting, and an organization disspirited. Because companies have so much data available to them, the circle may be so big it’ll look like a vector, a direction, for awhile, but sooner or later data will drive you right back to where you began.
A recent NPR story about racial discrimination in online dating points out how OKCupid’s sophisticated data analytics can’t tell two people what they need to know about one another for a romance to blossom, especially across different cultural or racial boundaries. As an interviewee puts it, “The good stuff begins where the data ends.” What’s the good stuff? The seduction. The playfulness. The chemistry. The newness. The possibilities. The romance.
If it’s like this for two individuals trying to figure out if they have a future together, how much more complex it is for a brand trying to connect with its customers, a company wanting to champion diversity, or a community trying to engage its citizens? Immensely more complex. No matter how much data you have on hand, the good stuff always begins where the data ends. The romancing can only happen if you’re willing to honor stories that co-exist with data.
Think of data and story as inextricably entwined, two sides of a coin. Data without storytelling to give it life is like trying to start a fire without a spark. It’s lifeless. Flat. Uninspiring. On the flip side, storytelling that doesn’t respect data is propaganda. It manipulates and ultimately disappoints when the illusion evaporates. Imagine being on an OKCupid dinner date with a person who tells fascinating stories but doesn’t share any information about himself. Check, please! It’s data–where a person went to school, how they grew up, what they do for a living, what music they like–that provides authentic points of connection, and avenues for sharing. No one tells a credible story without credible data.
Because there’s so much data–so many tools to produce it, visualize it, parse it, and analyze it–companies and communities tend to be over-reliant on it, simply because of its availability and abundance. In order to optimize the value of their data, they need a storytelling process that’s just as lively as their data gathering process. Storytelling that can absorb and contextualize what’s commonly referred to as Big Data. The old garden-variety linear storytelling, designed for channels and not networks, made popular by entertainment, simply isn’t up to the task. Having only one beginning, middle and end to your story is woefully insufficient. Your story needs multiple beginnings, middles and many possible endings. Otherwise it’ll get swamped by all your data.
Other characteristics of storytelling that can be paired effectively with Big Data:
- It’s highly improvisational, responsive and generative. It accounts for serendipity.
- It bridges the virtual and the physical worlds.
- It speaks different functional languages, operates in multiple genres.
- It accounts for multiple frames of time. Clock time and opportunity time (which doesn’t arrive on a schedule) are weighted equally.
- It is iterative. It can change from one day to the next without being inconsistent.
- It uses game structure to explore themes. We call these game structures ‘story engines.’