When I attend conferences involving scientific and technical topics, I still get lost at the immensity and busyness of many of the speakers’ presentations. What more if the audience is composed of laypeople? They will probably be drowned by the figures, graphs, and charts.
This is where the art and science of data storytelling come in. It is a structured approach for communicating insights from a dataset using narratives and visualizations.
Data storytelling gained popularity in 2010 when data science started to move into the mainstream. In the Philippines, it became fashionable in 2015 alongside the concepts of digital transformation, design thinking and analytics. However, it quickly died as a popular topic in conferences because it was presented as an esoteric art that required a great “story.”
It is both an art and a science. There is a methodology to it — which can be learned — while infusing it with an artsy side. Data storytelling is the intersection of three elements: the visual, the story and the data.
We, humans, always look for visuals to perceive information. Our brain has a special part called the visual cortex, located in the back of the head, that processes the visual information we see, helping us grasp information very quickly.
The way we perceive visuals follows gestalt principles of perception. One is proximity, i.e., objects that are close together or connected are perceived as a group. Another is similarity, where objects that share similar attributes, color or shape are perceived as a group. The third is continuity, i.e., objects that appear to have a boundary or continuation around them are perceived as a group. Then there is closure, i.e., open structures can be easily perceived as closed and complete. These explain the phenomenon of pareidolia or the human ability to see shapes or make pictures out of randomness.
Since the dawn of history, humans have combined visuals with stories to convey messages. This is what we call art, manifested in elaborate sculptures, paintings and structures.
The advent of information technology in the 1980s ushered in the growth of data. In 1985, Microsoft launched Excel, a spreadsheet application where data could be organized in columns and rows and manipulated to create graphs.
The graph is the intersection between visuals and data, which has helped humans convey messages about datasets. With advances in visualization technology, graphs have been transformed to convey more messages through other visualization techniques. As an example, a tree map is a very compact visualization that allows an exceptionally large amount of data to be viewed in a small space.
The need to effectively persuade, influence and motivate an audience with the intersection of data and story was necessitated by the onset of the internet, mobility and social media. This is what we call a tale, a narrative or story that is any account of connected events presented to a reader or listener in a sequence of written or spoken words or pictures.
The intersection of story, visual and data is what we term data storytelling. It is the infusion of art, graph and tale to deliver and convey a powerful message. The narrative construction in data storytelling consists of conveying the ideal state, presenting the reality and the problem, offering the solution and outlining the next steps. It shows good visualization together with a narrative to convey the answer clearly and concisely.
Data storytelling is both an art and a science that anyone can learn and practice.
The author is the founder and CEO of Hungry Workhorse Consulting, a digital and culture transformation consulting firm. He is a fellow at the US-based Institute for Digital Transformation and teaches strategic management in the MBA Program of De La Salle University. The author may be emailed at rey.lugtu@hungryworkhorse.com.