Beyond the Spreadsheet: The Art and Science of Data Storytelling

Weaving stories out of data threads

An abundance of data coinciding with the continued development of brute computing power in a hat-tip to Moore’s Law has led to much interest in the potential of data analytics. While much has been made of the ‘hard,’ left-brained use of data using analytics and algorithms, the true potential of data might lie in the softer, right-brained realm through storytelling using visualization to attract and retain attention, influence decisions and eventually help make better choices; more so given the proliferation of data, which is not exactly a good problem to have. Cole Nussbaumer Knaflic, the author of Storytelling with Data: A Data Visualization Guide for Business Professionals, says, “Having all the information in the world at our fingertips doesn’t make it easier to communicate: it makes it harder.”

The potential utility of data and analytics is unarguably massive (a 10% increase in data usability could increase the average Fortune 1000 company’s revenue by over $2 billion, according to research by the University of Texas, Austin), though two essential questions constrain it:

1.       How do you use the data?

Spreadsheets, algorithms, and mathematical calculations analyze data and glean insights. However, do all influencers and decision-makers have the skill sets first to understand these tools, use them to their potential, and understand the output? Answer: only sometimes. The old maxim of ‘Garbage In – Garbage Out’ applies here – apart from the quality of the data itself, the tools used to analyze it need to fit the need to be of any use.

2.      More importantly, how do you understand and use what the data have to say?

Interpreting the output is done by “experts” who may have a limited field of vision. Ultimately, findings must be understood by people connected with the decision in a business context. For example, a team of data scientists comes up with conclusions on customer segmentation in a new market that looks both copious and slick. Whether the marketing team can make practical use of it for on-ground strategies is an altogether separate issue.

The first question can be left in the capable hands of data scientists. It’s the second question that’s the more substantial one if data analytics is to realize its full potential.

Data-driven decision-making relies on persuasion resulting from creative visualization of the data and its analysis in creating a coherent storyline. Such an approach combines the more complex analytical aspects with the softer, psychologically convincing abilities of storytelling, leading to more confidence and better clarity in decisions. But why stories, and how do you weave them?

Storytelling is a fundamental aspect of being human, and that’s so not just because no other species we know of indulges in it! According to cognitive psychologist Jerome Bruner, we are 22 times more likely to remember a fact when it has been wrapped in a story. Stories convey information, make it easier to understand the conveyed information, and the understanding eventually makes it memorable. Storytelling has continued through millennia and has even greater relevance in a data-driven world where it is easy to get overwhelmed, paralyzed, misled, and off-tracked by information. Humans have always created internal narratives to make sense of the world, and these have become even more essential in the face of constant data storms.

Image credit: https://quotefancy.com/ 

Creating a compelling storyline using data

If a coherent storyline could tie in with the ‘narratives’ data created in our minds, enhance their clarity, and refine expectations of their outcomes, then we could have something powerful in our hands, something far more potent than analytics alone. This storyline goes beyond the cursory yet ubiquitous graphs that populate reports and presentations. Merely including this visual outline of information is neither effective nor sufficient for conveying your message. Following a structured approach helps, and some universal rules allow:

1.      Start with the end in mind: Develop your storyline, what it contains, what it needs to convey, and to whom before you start. Each data point, graph, infographic, and text box must follow this narrative or context.

2.      Declutter: Two pitfalls in developing a good storyline are a) using more data and visuals than is necessary; and b) digressing. The temptation is genuine, given the stacks of data and the glut of visualization tools available. Please don’t fall for it and declutter till total clarity emerges with minimal information. As Einstein said, “If you can’t explain it simply, you don’t understand it well enough.”

3.      Choose your tools wisely: Even the most common off-the-shelf software offers multiple visualization tools, such as charts, maps, tables, and infographics, that are easy to create with little training. Choose the type of visualization that best fits the data you are presenting, highlight statistics, comparisons, and trends in an interesting way, and aligns with your story and narrative. For example, interactive or static maps can be great for discussing new market entry statistics rather than plain tables

4.      Use the right colours: Colour is an important element of storytelling with data visualization. Colours help emphasize your key points, direct flow and attention and make information easy to understand. Colour contrast is a great way to make information look both good and legible

5.      Follow elements of good design: Several principles of good design apply to any design endeavour, and these principles will serve you well in your storytelling using data. These include, besides the choice of colour, a visually balanced layout, the correct hierarchy of information, alignment of design elements, repetition that helps to create a cohesive and unified design, the grouping of related design elements together that helps convey relationships between different pieces of information, and white space that improves readability

6.      Iterate: Finally, get feedback on your storyline from people you can rely on and iterate it based on feedback. Apart from getting inputs from people who might know better, this also gets you out of the echo chambers that tend to develop while working alone

Storytelling with data is part science and part art. The best practices listed here cover both aspects to varying degrees, while you need to use your artistic license in your context. Most of all, remember that the core structure of storytelling applies fully and completely to the data context as well: craft your story with a clear beginning (‘the plot’), a tight middle (‘twists’ or where you consider alternative ideas), and an end (a clear call to action). Go, tell your story.