Seeing the Big Picture

In my role as a professor, there is something I do at the beginning of each semester. The first class of any course is devoted to informing my students of just what the course entails: I give them the big picture. Depending on its clarity the students decide whether to take or drop the course. 

“When leadership brings clarity, decisions become unmistakable.” –Lolly Daskal

In every aspect of our daily lives we are bombarded by data from every direction. We can’t use all the data we collect, but we apply our own intelligence and judgment when a decision has to be made. Our brains have to process this influx of disjointed data, editing them as we go. This is facilitated by our intuition and imagination.

As with visual information where one can visualize a picture even though some of the pixels are missing, our imagination is used to fill in the gaps in the available patterns of non-visual data, letting us draw conclusions and make judgments based on uncertain and incomplete information. How accurate is the big picture that we are drawing? To what degree is it influenced by our moods and other subjective factors?

“One person’s data is another person’s noise.” – K.C. Cole 

Data are instances of basic events and existences. The one that is favored tends to survive and matures just like wine. Storytelling is a major way to help us render data meaningful, as it provides a soul and context to our data. 

Things get done only if the data we gather inform and inspire us and others. Our goal, therefore, is to turn data into information, and information into insight. However, with too little data, we are unable to make any conclusion that we trust. Even with loads of data, some inferences may not be correct. Collecting a mountain of data should not be the goal; it’s to create a clear and trustworthy big picture that matters. 

“Facts do not cease to exist because they are ignored.” – Aldous Huxley 

What is now called “big data” has become part of everyone’s life. Current communication systems ravenously collect information about people and businesses. We all have volunteered volumes of our personal data through social media services in addition to loads of geo-spatial data arising from the tracking of our smart phones. 

Big data can be used for the extraction of some generalities that are useful in some social and business fields. For instance, the discovery of previously unknown market segments, such as men driving home from work stop to buy diapers and beer.

However, Big Data is not only about the extraction of generalities it could identify individuals, their names, birth dates, and take advantage of this particular information. An unfortunate scenario is when the collected data leads to information falsely associated with us such as when a credit agency refuses to give us a loan because we wrongly fit an obscure violation model.

Also big data could be used to analyze current and historical facts and behavior to make predictions about future events. An embarrassing example for predictive analysis is when social media services know that your daughter is pregnant before you do.

Tell the story

Hence, in order to bring our data to life we need to effectively tell its story. Big data storytelling, like any other kind of storytelling, has certain rules that can determine its success or failure. Here are the four most important ones:

1. Concentrate on the essence of your story and skip the unnecessary details. Simplify and combine data. “The ability to simplify means to eliminate the unnecessary so that the necessary may speak.” –Hans Hofmann
2. Disregard the obvious as no one is interested in simple facts. "He who would search the pearls must dive below." – John Dryden
3. Summarize don't refine or twist facts to suit your own theories. There is a natural tendency to exploit big data and ignore that it’s illegal to misuse it. This can result in faulty inferences with some potential negative outcomes that could extend far beyond the individual, but to affect the social, economic, and political sectors.
4. Empathize with your audience. Finish your story within the time limit and let go even if it’s not perfect. Old information is of little if any value. Remember, your readers can always extrapolate from your story.

Successful interpretation of big data requires efficient storytelling. Without a human interface, data will only be a major source of confusion and false interpretation. It’s up to us to know how, why and when to use it.