How BI Brings Data Storytelling to Life | Defined Ventures, Inc.

Storytelling has been an integral part of human existence for as long as humans have existed. It’s how we preserve our history, share our lore, and and pass important lessons down to the people who out survive us. Most people can agree that without storytelling, humanity would simply not be where it is today.

“Okay,” you’re thinking. “Sure, storytelling is great. I read books all the time. Now what does this have to do with business?”

Stay with us for just a few minutes; we’re going to explain.

Data Visualization IS Storytelling

The first and most critical point we must make in this article is that there is virtually no core difference between historical storytelling and data visualization. Although each process shares a different type of data, both have the same common goal. That goal is to share information we feel is critical to advancement in a way that attracts attention and engages the listener.

In the case of oral storytelling throughout history, it was humans sharing important lessons about survival. In the case of business, it’s data visualization departments sharing important statistics and numbers that may improve the business’s chances of survival. Not really so different from this perspective, is it?

But that’s not how most people see it because the content in business storytelling is so much different. Most of us see it as numbers, information, and little more than hard facts, taking it at face value instead of using it to create a story. When that happens, businesses really lose out because the content is not only boring, but also fails to communicate what’s important.

Cole Nussbaumer Knaflic on Storytelling With Data

Author and Google data visualization specialist Cole Nussbaumer is a true data visualization artist. She makes magic out of simple numbers and statistics, drawing people in and making it easier to communicate critical information. To give you a concrete example of why data visualization has to be about so much more than just presenting numbers, we’ll turn to her video, “Storytelling with Data”  from Talks at Google.

About halfway through the video, Cole stops and asks people to count threes from a projector screen. What she pops up onto the screen is a solid 14 x 4 grid of pale grey numbers packed tightly together. There are six threes spread throughout the grid, but it takes the audience nearly a full minute to come to that conclusion.

Next, she asks the audience to do the same thing – but this time, she pops the same grid up with all of the threes bolded. Instantly, the audience can see what’s important and process it, rather than struggling through the maze of numbers.

This exercise in pre-attentive processing is, in many ways, exactly how storytelling in business intelligence works.

The Art of Transforming Data Into Business Intelligence

We know that data visualization should communicate important information in a way that’s easier to digest and use (without being boring). Now: how exactly can you make that happen? It’s just like any other art form – it takes time, practice, and an understanding of the basic theories that lead to success.

From playing with color to correlations and decluttering, here’s how you can make your data work for your business.

Use the Color Theory to Your Advantage

Color matters to the human brain. It differentiates objects, creates depth, and can even allow us to identify differences – the same is true when it’s used correctly in data visualization.

Cole’s excellent example outlined above is, in fact, a demonstration of how effective color can be in data visualization. Using hue, intensity, and shade, we can highlight or minimize data to “pull forward” what’s most important. The result is that the eye is immediately drawn to those more important elements without getting lost on the screen or page.

Color can also carry meaning or tone – that’s why breast cancer organizations use pink. Blues and greys, on the other hand, often carry intonations of authority, business, or professionalism. Greens, naturally, create an “environmental” or natural feel, as do earth tones.

Don’t forget that text color can also be beneficial – highlighting a single word throughout text or a few phrases will make those phrases stick. This is a common tactic in sales, training, and education.

Of course, color can be a detractor, too. Using too many colors, colors that clash, or colors in the wrong patterns can make your data more confusing. It’s better to use color to highlight, draw the eye in a specific direction, or to draw attention to specific area of your visualization.

Choose the Right Data Visualization Format

Data visualization must be structured correctly in order to be useful. Without that proper structure, information gets lost and it becomes overwhelming to try and pick through everything to find what you need.

This is an area where BI visualization really does become similar to writing a book. In order to achieve true storytelling in data visualization, you have to determine what story format your data is asking for.

Some stories are best written as short stories, while others demand a a trilogy format. Still others make better comics or even graphic novels. Likewise, some data works best in a line graph, while other data is better suited to column, bar, or scatter plot graphs – or even infographics!

Remember that choosing how you visualize your data isn’t just about the data itself; it’s also about who you’re sharing your visualization with. Much like an author, you do need to read your audience and figure out how they best digest information. A design team, for example, will naturally gravitate to color or design, while an accountant may prefer a more stripped-back approach with simple text highlights.

Tell a Good Story; Be a Great Storyteller

Lastly, even if you use color artistically and choose the right format, you still need to lay your data out in storytelling style to succeed. There are five main points you have to hit to make this work.

First, find the story. What is it people want to know and why does your data matter? What is the result (ending) that you want to achieve? Data visualization, like stories, has an introduction, a problem, and hopefully, a solution.

Next, find ways to connect with your audience. Who are they? Why do they care? Why does this data matter to them, be it for sales or as part of a business meeting? Make it obvious why they should pay attention and qualify why it matters.

Use graphics smartly – not too much, and not too little. Avoid cramming too much in a single segment of visualization. Like novels, if there’s too many stories going on at once that don’t weave into each other, it’s easy to get lost.

Revise your visualization by honing in on the main issues you are attempting to visualize. Find what matters most, identify it, draw it out, and make it grab attention. Help the audience draw complex conclusions or make correlations when it isn’t obvious, but don’t tell them what they should think. Data should flow from one point to the next and link up logically.

Finally, encourage interactivity. Interactive storytelling is so much more interesting than flat, dry words or numbers on a stage. If there’s a way for you to allow your audience to play with the data, move it around, or manipulate it, make it happen.

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